Abstract: An image processor and a method therein to provide a target image for evaluation with an object detector. The method comprises: obtaining a source image captured by a camera and depicting an object, and applying an inverse pixel transform to each target pixel of a target image to determine one or more source pixels located at a position in the source image corresponding to a position of each target pixel in the target image. The method further comprises assigning, to each target pixel, a target pixel value determined based on one or more source pixel values of the determined one or more source pixels located at the corresponding position, thereby is a size c in the target image of the depicted object of a specific object type normalized in at least one size dimension. Thereafter, the target image is fed to an object detector for evaluation.

Abstract: Disclosed are systems, devices and methods for quantifying unique features of an object such as an artistic work to identify and authenticate the object and specific characteristics thereof using multi-spectral diagnostic characterization techniques and analytical algorithms. In some aspects, a method for creating an identification for an object includes acquiring image data of an object in two or more electromagnetic spectrums along a coordinated array of sample regions of the object; analyzing the acquired image data to produce a quantitative data set including specific characteristics of the object associated with the two or more electromagnetic spectrums for each sample region; generating a digital identification associated with a unique data fingerprint, based on the specific characteristics, in which the digital identification solely corresponds to the object; and storing the generated digital identification.

Abstract: A system and method for identifying ground types from one or more interpolated covariates. The method proceeds by accessing soil composition information for plots of land, in which the soil composition information includes measured soil sample results, environmental results, soil conductivity results or any combination thereof. The method continues by identifying covariates from the soil composition information. Subsequently, the method interpolates covariates associated with different locations with an interpolation training model. Voxels are generated that are each associated with interpolated covariates having a corresponding geographical location. The method trains a random forest training model with the interpolated covariates. The voxels traverse the trained random forest model to identify clusters of voxels that are co-associated. The method identifies a ground type by combining the co-associated clusters.

Abstract: A system and method for visualizing one or more crop response surfaces. The system includes a geospatial database associated with a crop prediction engine. The geospatial database receives soil composition information for plots of land. The crop prediction engine identifies covariates from the soil composition information, which has a feature matrix. The crop prediction engine generates a multi-dimensional covariate training data set from the covariates. The crop prediction engine then applies the multi-dimensional covariate training data set to a machine learning training model to generate at least one predictive crop-yield predictive model. The crop prediction engine ranks covariates having feature set interactions. Subsequently, the crop prediction engine determines a dominant crop-yield feature set interaction from the ranked covariates having feature set interactions. The crop prediction engine generates a crop response surface from the dominant crop-yield feature set interaction.

Abstract: Methods and systems used for the classification of a crop grown within an agricultural field using remotely-sensed image data. In one example, the method involves unsupervised pixel clustering, which includes gathering pixel values and assigning them to clusters to produce a pixel distribution signal. The pixel distribution signals of the remotely-sensed image data over the growing season are summed up to generate a temporal representation of a management zone. Location information of the management zone is added to the temporal data and ingested into a Recurrent Neural Network (RNN). The output of the model is a prediction of the crop type grown in the management zone over the growing season. Furthermore, a notification can be sent to an agricultural grower or to third parties/stakeholders associated with the grower and/or the field, informing them of the crop classification prediction.

Abstract: Techniques are described for a multiple-phase process that uses machine learning (ML) models to produce a texturized version of an input image. During a first phase, using a pix2pix-based ML model, an automatically-generated image that depicts structured texture is generated based on an input image that visually identifies a plurality of image areas for the structured texture. During a second phase, a neural style transfer-based ML model is used to apply the style of a style image (e.g., a target image from the training dataset of the pix2pix-based ML model) to the texture image generated at the first phase (the content image) to produce a modified texture image. According to an embodiment, during a third phase, the generated texture image produced at the first phase and the modified texture image produced at the second phase are combined to produce a structured texture image with a moderated amount of detail.

Abstract: An information providing system provides information relating to dirt in a drain pan of an air conditioner. The information providing system is provided with a computer which is connected to a camera and a user terminal. The computer acquires image data of a target object imaged by the camera, identifies a dirty region in the image data, creates dirt-related information in which the dirty region is highlighted in the image data, and outputs the dirt-related information to the user terminal.

Abstract: Methods and systems for high-resolution image inpainting are disclosed. An original high-resolution image to be inpainted is obtained, as well as an inpainting mask indicating an inside-mask area to be inpainted. The original high-resolution image is down-sampled to obtain a low-resolution image to be inpainted. Using a trained inpainting generator, a low-resolution inpainted image and a set of attention scores are generated from the low-resolution image. The attention scores represent the similarity between inside-mask regions and outside-mask regions. A high-frequency residual image is computed from the original high-resolution image. An aggregated high-frequency residual image is generated using the attention scores, including high-frequency residual information for the inside-mask area. A high-resolution inpainted image is outputted by combining the aggregated high-frequency residual image and a low-frequency inpainted image generated from the low-resolution inpainted image.

Abstract: A system includes: an acquiring unit that acquires an image of an n-dimensional symbol; a first image capturing unit that captures an image of a random pattern on a surface of an object; a storing unit that stores the image of the n-dimensional symbol and a first image that is the image of the random pattern captured by the first image capturing unit in a manner that the images are associated with each other; a second image capturing unit that captures an image of a random pattern on a surface of an object; a matching unit that performs matching of the image captured by the second image capturing unit against the first image stored by the storing unit; and a displaying unit that displays the image of the n-dimensional symbol associated with the first image stored by the storing unit based on the result of the matching.

Abstract: System, methods, and other embodiments described herein relate to predicting effects of a stimulus on a particle or other material structure. In one embodiment, a method includes receiving a segmented image of a particle that identifies at least semantics of the particle and associated characteristics according to subregions of the particle. The method includes analyzing, using a stimulus model, the segmented image to predict changes in the particle associated with applying the stimulus to the particle. Analyzing the segmented image includes generating a predicted image identifying characteristics, semantics and other properties of the particle according to the changes. The method includes providing the predicted image as an electronic output.

Abstract: The present disclosure discloses an image processing method, apparatus, and a non-transitory computer readable medium. The method can includes: acquiring a three-dimensional (3D) model and original texture images of an object, wherein the original texture images are acquired by an imaging device; determining a mapping relationship between the 3D model and the original texture images of the object; determining, among the original texture images, a subset of texture images associated with a first perspective of the imaging device; splicing the subset of texture images into a spliced texture image corresponding to the first perspective; and mapping the spliced texture image to the 3D model according to the mapping relationship.

Abstract: Disclosed are an apparatus for controlling a reverse drive of a vehicle and a method of outputting warning thereof. The apparatus for controlling a reverse drive of a vehicle includes a sensor that senses whether a reverse shift is input, a lamp that outputs a reverse guide pattern to a ground surface, and a controller that controls the lamp to output the reverse guide pattern when the reverse shift is input and determine whether the vehicle is able to be reversed based on whether the reverse guide pattern output to the ground surface is changed.

Abstract: The present invention belongs to the technical field of constructional engineering safety detection, and provides a method for detecting hollowing of an exterior wall finish layer. The method for detecting a defect of a facade finish layer of a building proposed by the present invention can realize remote detection in the on-site detection operation and avoid high-altitude hazardous operation of personnel, and is simple and convenient in operation. In data analysis and processing, the method not only can overcome the subjectivity and the instability caused by manual color identification of a temperature image, but also can realize batch processing of image analysis through software or conduct real-time detection and analysis.

Abstract: A processing apparatus includes an acquisition unit configured to acquire a plurality of pieces of color image data respectively representing a plurality of color images, a determining unit configured to determine a degree of correlation between at least two color values among a plurality of types of color values included in each of a plurality of pixel values corresponding to a pixel position in the plurality of color images, and a determination unit configured to determine, based on the determined degree of correlation, whether a feature related to a direction of light reflected from an object appears in the plurality of pixel values corresponding to the pixel position.

Abstract: The present invention provides an anomaly detection method and apparatus based on a neural network which can be trained on undamaged normal vehicle images and able to detect unknown/unseen vehicle damages of stochastic types and extents from images which are taken in various contexts. The provided method and apparatus are implemented with functional units which are trained to perform the anomaly detection under a GCAN model with a training dataset containing images of undamaged vehicles, intact-vehicle frame images and augmented vehicle frame images of the vehicles.

Abstract: A sensor includes a substrate, a reference electrode provided above the substrate, a lower electrode provided above the reference electrode via an insulating film, and an upper electrode provided above the lower electrode via a physical quantity detecting film. The upper electrode and the lower electrode form a parallel-plate-type detection capacitor, and the lower electrode and the reference electrode form a parallel-plate-type reference capacitor.

Abstract: The disclosure lies in the field of coding image data, scalable in image resolution, such that one or more successive downsamplings are performed from a source signal of maximal image resolution to a minimal image resolution, in order to encode a base layer (L0) corresponding to this minimal resolution, the base layer (L0) serving as a reference for one or more enhancement layers (L1, L2) to be used for decoding at a terminal having a screen of higher image resolution than the minimal image resolution. From said successive downsamplings, the base layer (L0) and the one or more enhancement layers (L1, L2) are constructed, and then an encoded bit stream is prepared in order to be transmitted, comprising data of the base layer and of the enhancement layer or layers. In particular, the downsampling step comprises the application of an adaptive low-pass filter to the image data from the downsampling.

Abstract: An information processing apparatus includes an acquisition unit configured to acquire a plurality of captured images of a traveling surface where a movable apparatus travels, each of the captured images including distance information in a depth direction transverse to the traveling surface, the plurality of captured images having been captured using a plurality of stereo image capture devices, and an image processing unit configured to stitch together the plurality of images of the traveling surface captured by the plurality of stereo image capture devices by identifying partially overlapping portions of one or more pairs of the images captured by respective stereo image capture devices which are adjacent in a width direction of the traveling surface.

Abstract: The disclosure notably relates to a computer-implemented method for retrieving a similar virtual material appearance from a database. The method comprises providing a database including virtual material appearances associated to an appearance signatures computed from values representing at least one of a structure, a reflection and a color of the associated virtual material appearance. The method further comprises providing a first appearance signature associated to a first virtual material appearance. The method further comprises identifying one or more virtual material appearances similar to the first virtual material appearance by comparing the first appearance signature with appearance signatures respectively associated to virtual material appearances in the database. The method improves retrieval of virtual material appearances.

Abstract: A method for automated gear contact pattern verification includes applying a colored powder to at least one gear to be meshed to form contacts on at least one gear tooth of the at least one gear, and using the smartphone, capturing images of the at least one gear tooth. A matching algorithm run on the smartphone may include identifying bounding points of a yellow portion of the at least one gear tooth, the bounding points including a midpoint of the yellow portion; identifying a gear mesh area between the bounding points and a midpoint of the gear mesh area; and determining a deviation in the midpoints of the yellow portion and gear mesh area, wherein the deviation may between approximately 25% and 80%. The test results are displayed on the smartphone, the test results including at least an indication of pass or fail.

Abstract: A method for generating user feedback information from a shave event associated with a user. A shaving razor is provided to user. The shaving razor includes a handle, a hair cutting implement connected to the handle, at least one motion sensor in the handle, a hair cutting implement displacement sensor associated with the handle, a communication device associated with the handle and a power source associated with the handle. The power source powers the at least one motion sensor, the hair cutting implement displacement sensor and the communication device. Shave event data associated with the user during a shave is collected from the at least one motion sensor and the hair cutting implement displacement sensor. The shave event data is processed to generate user feedback information.

Abstract: Disclosed are systems, devices and methods for quantifying unique features of an object such as an artistic work to identify and authenticate the object and specific characteristics thereof using multi-spectral diagnostic characterization techniques and analytical algorithms. In some aspects, a method for creating an identification for an object includes acquiring image data of an object in two or more electromagnetic spectrums along a coordinated array of sample regions of the object; analyzing the acquired image data to produce a quantitative data set including specific characteristics of the object associated with the two or more electromagnetic spectrums for each sample region; generating a digital identification associated with a unique data fingerprint, based on the specific characteristics, in which the digital identification solely corresponds to the object; and storing the generated digital identification.

Abstract: This ultrasonic inspection device, for inspecting a packaged semiconductor device, is provided with: an ultrasonic transducer which outputs ultrasonic waves to a semiconductor device; a receiver (a reflection detection unit) which detects reflected waves of the ultrasonic waves reflected on the semiconductor device; a stage which moves the positions of the semiconductor device relative to the ultrasonic transducer; a stage control unit which controls driving of the stage; and an analysis unit which analyzes the reaction of the semiconductor device to the input of the ultrasonic waves from the ultrasonic transducer. The stage control unit controls the distance between the semiconductor device and the ultrasonic transducer on the basis of a peak occurring in time waveform of the reflected wave detected by the receiver.

Abstract: Implementations described and claimed herein provide localization systems and methods using surface imaging. In one implementation, a raw image of a target surface is captured using at least one imager. The raw image is encoded into a template using at least one transform. The template specifies a course direction and an intensity gradient at one or more spatial frequencies of a pattern of the target surface. The template is compared to a subset of reference templates selected from a gallery stored in one or more storage media. A location of the target surface is identified when the template matches a reference template in the subset.

Abstract: Described herein are systems, methods, storage media, and computer programs for tracking a plurality of feature points in a first image and a second image. In one embodiment, a first layer of a first image pyramid for the first image and a first layer of a second image pyramid for the second image are obtained. Based on expected pixel locations of the plurality of feature points in the first layer of the second image pyramid, a feature point is selected from the plurality of feature points. For the feature point, a first pixel in the first layer of the first image pyramid is determined, and a second pixel in the first layer of the second image pyramid is determined, where the first pixel substantially matches the second pixel.

Abstract: A visualization module of an imaging system having a 3D geocellular model generated for illustrating rock types within a subterranean formation. The visualization module can determine that cells of the 3D geocellular model are visible to a field of view for a viewing user. For each cell determined to be visible, the visualization module can determine a rock type for the cell and that one or more faces of the cell are visible. For each face determined to be visible, the visualization module can determine an orientation of the face; determine that an image corresponds to the determined orientation and determined rock type; and apply the image to the face of the cell in the 3D geocellular model.

Abstract: A system for determining a level of debris accumulation in a region adjacent to at least one blade of a razor cartridge. The system includes a sensing unit to detect a measurement parameter which is one of an amount of light reflected from at least one area adjacent to the at least one blade, and an image of the at least one area adjacent to the at least one blade. A processing unit compares the detected measurement parameter to at least one reference threshold parameter and determines a level of debris accumulation in the at least one area adjacent to the at least one blade based on an amount of deviation of the detected measurement parameter from the at least one reference threshold parameter. Information regarding the determined level of debris accumulation is provided by at least one of a light indication, an aural indication, and a haptic indication.

Abstract: The present disclosure provides a method, an apparatus, a device for evaluating image tracking effectiveness and a readable storage medium. The method includes: extracting feature points from a target image according to a predefined algorithm; determining first texture information for the target image according to the feature points; processing the target image according to a predefined processing policy to derive a contrast image, and determining second texture information for the target image according to the contrast image; and rating the target image according to the first texture information and the second texture information. In the solution provide by the present disclosure, the tracking effectiveness for the target image can be known without having to place the target image into any actual product, nor having to wait until the product has been finalized before the target image tracking effectiveness is determined. Moreover, efficiency can be enhanced when evaluating image tracking effectiveness.

Abstract: A process operable using a computerized system (300) grades the clarity of a diamond (315, 400) as a function of internal defects within its body (315, 400). The computerized system (300) includes an optical image acquisition device (310), a processor module (320) and an output module (340) operably interconnected together. The process includes the steps of (i) acquiring via an optical image acquisition device (310) a plurality of top view images of a diamond (315, 400); (ii) in a processor module (320), detecting defects within the body of the diamond (315, 400); and (iii) from an output module (340), providing a signal indicative of the clarity grade assigned in (ii).

Abstract: A shaving system including a shaver handle and one or more sensors. The one or more sensors may be configured to detect a hand of a user on the handle and to generate one or more sensor signals. The system may also include a processor operably coupled to the one or more sensors and having at least one algorithm stored thereon for analyzing the one or more sensor signals to determine a grip of the user's hand on the handle. They system may further include an indicator operably coupled to the processor, and the indicator may be configured to provide at least one of feedback or a recommendation to the user based at least in part on the grip of the user during a shaving session.

Abstract: Implementations include receiving an input image including a face, processing the input image through a global transformation network to provide a set of global transformation parameters, applying the set of global transformation parameters to the input image to provide a globally transformed image, processing the globally transformed image through a global representation learning network to provide a set of global features, processing the set of global features through a part localization network to provide a set of part localization parameters, applying the set of part localization parameters to the globally transformed image to provide a locally transformed image, processing the locally transformed image through a part representation learning network to provide a set of local features, and outputting a label representing at least one attribute depicted in the input image based on fusing global feature(s) from the set of global features, and local feature(s) from the set of local features.

Abstract: A method for generating user feedback information from a shave event associated with a user. A shaving razor is provided to user. The shaving razor includes a handle, a hair cutting implement connected to the handle, at least one motion sensor in the handle, a hair cutting implement displacement sensor positioned in the handle, a communication device positioned in the handle and a power source positioned in the handle. The power source powers the at least one motion sensor, the hair cutting implement displacement sensor and the communication device. Shave event data associated with the user during a shave is collected from the at least one motion sensor and the hair cutting implement displacement sensor. The shave event data is processed to generate user feedback information.

Abstract: A measurement method for micro topography and roughness of internal surface of gap belongs to the technical field of precision measurement and is realized based on a measurement system which comprises a PC, a controller, a flexible mechanism and a measurement thin film. The measurement thin film has a copy function and is bonded to the flexible mechanism. The PC is connected with the flexible mechanism through the controller to control the flexible mechanism to expand or contract. The measurement method can effectively solve the measurement problem of the micro topography and surface roughness of the internal surface of the gap with a narrow inlet size. The method is simple and easy to operate, and the device is easy to carry, low in cost and high in measurement accuracy.

Abstract: In a method, a computer and a medical computer for automatic failure analysis in order to provide a cause of failure of the medical imaging apparatus during operation, input data are read into the computer that include raw data or image data, acquired by the imaging apparatus. A set of performance indicators in the input data is calculated by the computer. A trained neural network system is accessed with the calculated performance indicators, in order to provide result data that, in the case of a failure, identify a failure source.

Abstract: Implementations described and claimed herein provide systems and methods for surface monitoring. In one implementation, a target surface ahead of a vehicle is illuminated with light emitted from at least one light source. Image data of the target surface is captured from returns collected by at least one imager. At least one surface property of the target surface is measured using the image data. A set of friction metrics is generated from the at least one surface property. An estimated coefficient of friction for the target surface is determined from the set of friction metrics.

Abstract: The present disclosure discloses an image processing method, apparatus, and a non-transitory computer readable medium. The method can includes: acquiring a three-dimensional (3D) model and original texture images of an object, wherein the original texture images are acquired by an imaging device; determining a mapping relationship between the 3D model and the original texture images of the object; determining, among the original texture images, a subset of texture images associated with a first perspective of the imaging device; splicing the subset of texture images into a spliced texture image corresponding to the first perspective; and mapping the spliced texture image to the 3D model according to the mapping relationship.

Abstract: A method and apparatus for processing an image of fragmented material to identify fragmented material portions within the image is disclosed. The method involves receiving pixel data associated with an input plurality of pixels representing the image of the fragmented material. The method also involves processing the pixel data using a convolutional neural network, the convolutional neural network having a plurality of layers and producing a pixel classification output indicating whether pixels in the input plurality of pixels are located at one of an edge of a fragmented material portion, inwardly from the edge, and at interstices between fragmented material portions. The convolutional neural network includes at least one convolution layer configured to produce a convolution of the input plurality of pixels, the convolutional neural network having been previously trained using a plurality of training images including previously identified fragmented material portions.

Abstract: Methods and systems for collecting high definition images of spent firearm cartridges under different illumination conditions described herein. Features indicative of firing pin impact with each spent firearm cartridge are extracted and compared to features extracted from different spent firearm cartridges. The likelihood that the cartridges were fired from the same firearm is determined based on the differences between the extracted features. A cartridge fixture locates a spent firearm cartridge inside an imaging chamber illuminated by different combinations of illumination devices located in different locations with respect to the spent firearm cartridge. Collected images are filtered by a trained image feature filter to extract features indicative of a firing pin strike. Features extracted from different spent firearm cartridges are compared to determine the likelihood that the spent firearm cartridges were fired from the same firearm based on one or more error metrics characterizing feature differences.

Abstract: Systems and methods to analyze a person's social media photos or videos, such as those posted on Twitter, Facebook, Instagram, etc. and determine properties of their social life. Using information on the number of people appearing in the photos or videos, their ages, and genders, this method can predict whether the person is in a romantic relationship, has a close family, is a group person, or is single. This information is valuable for generating audiovisual content recommendations as well as for advertisers, because it allows targeting personalized advertisements to the person posting the photos. The described methods may be performed (and the advertisements or other content may be selected for recommendation) substantially in real-time as the user accesses a specific online resource.

Abstract: The present invention relates to projectiles and munitions, and more specifically to such in flight. More particularly the present invention relates to projectiles and munitions in flight equipped with one or more image sensors adapted for acquiring image data of the environment surrounding the projection or munition in flight. The present invention further relates to systems and methods for correcting or stabilizing motion effects and artifacts present in the image data related to the movement or motion of the projectile or munition in flight, including spin or rotation of the projectile or munition.

Abstract: A fingerprint detection device including a plurality of fingerprint sensing elements, and each fingerprint sensing element includes: a sensing electrode for forming a sensing capacitance from a relationship with a subject; an amplifier having a first input end connected to the sensing electrode and a second input end into which a bias signal, of which a potential is changed from a high level to a low level or from the low level to the high level during a fingerprint detection operation, is inputted; and a gain controller including a plurality of sub-feedback capacitances, the gain controller selectively connected between the first input end and an output end of the amplifier.

Abstract: According to an embodiment, a method of determining tool mark identity using machine learning may include: obtaining surface height data of at least two tool strip marks by photographing tool strip marks generated using at least two tools with a three-dimensional (3D) microscope; generating a data set by calculating a cross-correlation coefficient for the surface height data of the tool strip marks; separating the data set into a training set for machine learning training and a test set for verifying a machine learning result; performing the machine learning training to determine whether the tool strip marks are identical using the training set; and verifying a result of the machine learning training using the test set.

Abstract: The present disclosure provides systems and methods that measure soil roughness in a field from imagery of the field. In particular, the present subject matter is directed to systems and methods that include or otherwise leverage a machine-learned clod detection model to determine a soil roughness value for a portion of a field based at least in part on imagery of such portion of the field captured by an imaging device. For example, the imaging device can be a camera positioned in a downward-facing direction and physically coupled to a work vehicle or an implement towed by the work vehicle through the field.

Abstract: The present invention relates to the technical field of well logging interpretation. The present invention provides a method for determining the karst development degree of a reservoir, a computer readable storage medium and a device, and pertains to the technical field of well logging interpretation, the method comprising: extracting vertical denudation pore features and horizontal denudation pore features from electrical imaging logging image data of a undetermined reservoir, and counting well logging feature parameters; determining karst belts of the undetermined reservoir and classifying the karst development degree according to the vertical denudation pore features, the horizontal denudation pore features and the well logging feature parameters; and determining the available reservoir development degree of the undetermined reservoir according to the karst belts and the result of the classified karst development degree.

Abstract: The present subject matter at-least provides a system for measurement of topography of specular surfaces. The system comprises a set of indexed light-sources and a controller configured to drive the set of light-sources for irradiating a specular-surface by sequentially illuminating a plurality of sub-sets of the light-sources in accordance with a pre-defined encoding criteria. Further, at least one camera is provided to capture reflected light-radiation from the specular-surface and thereby generate a plurality of images in accordance with the sequential-illumination, such that each of the generated-image corresponds to a particular sub-set of illuminated light sources.

Abstract: Characteristic data of a relevant component is extracted from a component image captured by camera, and the extracted characteristic data is compared with reference characteristic data of multiple types of component registered in a database to distinguish a type of component for which the two sets of data match most closely. As a result of this, a power spectrum image is created by applying an FFT for each scanning line to a lead presence candidate region corresponding to a candidate for a lead being present in a component image distinguished as an odd form component. Further, an HLAC characteristic is calculated from the power spectrum image in order to extract a periodic characteristic of the power spectrum image, and a connector component with leads is distinguished from an odd form component by learning a characteristic amount of the LAC characteristic using an SVM.

Abstract: Disclosed are a method and/or a system for real-time analysis and marking of a target surface using a digital camera coupled marking device. In one embodiment, a master controller receives a real-time digital camera signal from the digital camera of a marking device communicatively coupled to the master controller. The master controller analyzes the digital camera signal using an image recognition algorithm, a machine vision algorithm, and a database and archives a visual state and an object design parameter of an object. The master controller compares the visual state of an object with a library of known visual states in the database to extract an associated marking pattern and a desired marking location of the object. The master controller generates and sends a marking command to a pin marker of the marking device. The pin marker engraves the marking pattern onto the object in real time.

Abstract: A control method of controlling an electronic device is provided. The control method includes sequencing the number of times of gains used by a fingerprint sensor of the electronic device when fingerprint unlocking of the electronic device is successful, and controlling the fingerprint sensor to directly use a gain with the maximum number of times to obtain a fingerprint image to conduct fingerprint unlocking.

Abstract: A generative adversarial network (GAN) system includes a generator neural sub-network configured to receive one or more images depicting one or more objects. The generator neural sub-network also is configured to generate a foreground image and a background image based on the one or more images that are received, the generator neural sub-network configured to combine the foreground image with the background image to form a consolidated image. The GAN system also includes a discriminator neural sub-network configured to examine the consolidated image and determine whether the consolidated image depicts at least one of the objects. The generator neural sub-network is configured to one or more of provide the consolidated image or generate an additional image as a training image used to train another neural network to automatically identify the one or more objects in one or more other images.

Abstract: Provided is a fingerprint identification system, comprising: a plurality of first pixel circuits; a first sensing circuit for sensing a contact capacitance and outputting a first output signal, where the first output signal contains a big signal component and a small signal component, and the small signal component correlates with a change amount of the contact capacitance; at least one second pixel circuit; a second sensing circuit for outputting a second output signal, where the second output signal is equal to the big signal component; and a differential amplifying circuit for amplifying a difference value between the first output signal and the second output signal so as to generate an amplifying output signal, where the amplifying output signal correlates with the small signal component.