Abstract: Systems, and method and computer readable media that store instructions for high-resolution face recognition.

Abstract: This application discloses a precoding method and apparatus, and an information transmission method and apparatus, and relates to the field of communications technologies, to help improve overall performance of a plurality of data streams corresponding to a same codeword. The precoding method includes: decomposing a channel matrix into a product of a matrix Q, a matrix R, and a matrix PH, where the matrix PH is a conjugate transpose matrix of a matrix P, both the matrix Q and the matrix P are unitary matrices, and the matrix R is an upper triangular matrix; and precoding to-be-sent data based on the matrix P.

Abstract: A method and system for processing thermal video images and thermal video images of patients, using a method of real-time demarcation of the macro aspect of the region of interest, generated by MIR and LIR electromagnetic wave emission and merging of the real image, with improvement of the image, also in real time, allowing for analysis of the micro aspect by means of NIR electromagnetic wave emission, for spectral identification of the sample by infrared vibrational spectroscopy. The method and system pertains to the fields of medicine, biomedicine, and electrical engineering.

Abstract: An example laser system includes a laser, a plurality of pulse stretchers coupled together in series, a feedback module, and a lens assembly. The plurality of pulse stretchers is configured to stretch pulse widths of laser pulses provided by the laser and to output stretched laser pulses. The feedback module includes a pulse delay comparator that is configured to compare a first laser pulse of the laser pulses to a corresponding first stretched laser pulse of the stretched laser pulses. The feedback module also includes a computing device that is configured to determine, based on a result of the comparing by the pulse delay comparator, an adjustment to a pulse stretcher of the plurality of pulse stretchers, and apply the adjustment to the pulse stretcher so as to modify a shape of a second stretched laser pulse of the stretched laser pulses.

Abstract: An electronic device is provided. The electronic device includes an input interface and a processor that performs noise removal processing on an image input through the input interface, obtains first information on a first texture block among a plurality of first pixel blocks included in the input image, obtains second information on a second texture block among a plurality of second pixel blocks included in the noise-removed image, obtains third information on maximum energy amount among energy amount of each of the plurality of second pixel blocks, and identifies whether the input image is an upscaled image based on the first, second and third information.

Abstract: Described examples relate to an apparatus comprising one or more image sensors coupled to a vehicle and at least one processor. The at least one processor may be configured to capture, in a burst sequence using the one or more image sensors, multiple frames of an image of a scene, the multiple frames having respective, relative offsets of the image across the multiple frames and perform super-resolution computations using the captured, multiple frames of the image of the scene. The at least one processor may also be configured to accumulate, based on the super-resolution computations, color planes and combine, using the one or more processors, the accumulated color planes to create a super-resolution image of the scene.

Abstract: A technique making use of a few-shot model to determine graphical features present in an image based on a small set of examples with known graphical features. Where a support set including a number of images that each have a known combination of graphical features, the image recognition can identify unknown combinations of those graphical features in any number of query images. In an embodiment of the present disclosure examples of a filled-out form are used to interpret any number of additional filled out versions of the form.

Abstract: An access control apparatus includes a sensor and an authentication circuit coupled to the sensor. The sensor detects eye movement of a user. The authentication circuit stores predetermined access code data corresponding to the user. The authentication circuit compares the detected eye movement of the user to the predetermined access code data. Based on the comparison indicating that the detected eye movement matches the predetermined access code data, the authentication circuit permits access beyond an access control point.

Abstract: A training method of a neural network, and a recognition method and apparatus using the neural network are disclosed. The recognition method using the neural network includes obtaining a feature vector generated from a hidden layer of the neural network, in response to data being entered to an input layer of the neural network, and determining a reliability of a recognition result for the data using the feature vector and clusters.

Abstract: The present technology relates to image signal processing. One aspect of the present technology involves analyzing reference imagery gathered by a camera system to determine which parts of an image frame offer high probabilities of—relative to other image parts—containing decodable watermark data. Another aspect of the present technology whittles-down such determined image frame parts based on detected content (e.g., a cereal box) vs expected background within such determined image frame parts.

Abstract: The embodiments of the disclosure provide a method for inputting characters with eye gazes, a host, and a computer readable storage medium. The method includes: providing a character inputting interface, wherein the character inputting interface comprises a first character set, and the first character set comprises a plurality of first characters; obtaining a first eye gaze position on the character inputting interface; and in response to determining that the first eye gaze position triggers a first specific character among the first characters, inputting the first specific character.

Abstract: A vehicle includes one or more cameras that capture a plurality of two-dimensional images of a three-dimensional object. A light detector and/or a semantic classifier search within those images for lights of the three-dimensional object. A vehicle signal detection module fuses information from the light detector and/or the semantic classifier to produce a semantic meaning for the lights. The vehicle can be controlled based on the semantic meaning. Further, the vehicle can include a depth sensor and an object projector. The object projector can determine regions of interest within the two-dimensional images, based on the depth sensor. The light detector and/or the semantic classifier can use these regions of interest to efficiently perform the search for the lights.

Abstract: An image processing apparatus includes a change detection unit configured to detect a phase change having a predetermined amount of change from phase changes in a subregion of an edge image having a predetermined resolution, a change amount adjustment unit configured to adjust the amount of change of the detected phase change, an adjusted image generation unit configured to generate an edge image having the predetermined resolution in which the amount of change of a motion change is adjusted based on the phase change in which the amount of change of the phase change is adjusted, and a region decision unit configured to decide a new subregion of an edge image having a new predetermined resolution based on the edge image having the predetermined resolution in which the amount of change of the motion change is not adjusted and the edge image having the predetermined resolution in which the amount of change of the motion change is adjusted.

Abstract: An image decoding method includes splitting a current block into a plurality of coefficient groups based on the current block is the non-square block, wherein the plurality of coefficient groups include a non-square coefficient group, obtaining coefficients corresponding to the plurality of coefficient groups based on a first scan order and a second scan order, wherein the first scan order represents a scan order among coefficients of the non-square coefficient group and wherein the second scan order represents a scan order among the plurality of coefficient groups, and reconstructing the image based on the coefficients.

Abstract: Disclosed are systems and methods including starting with a first number of images, generating a second number of images by digital operations on the first number of images, extracting features from the second number of images, and generating a classification model by training a neural network on the second number of images wherein the classification model provides a percentage likelihood of an image's categorisation, embedding the classification model in a processor and receiving an image for categorisation, wherein the processor is in communication with a POS system, the processor running the classification model to provide output to the POS system of a percentage likelihood of the image's categorisation.

Abstract: Methods, devices and non-transitory computer-readable storage medium for processing a sequence of respective top view images of a same terrestrial location are provided. One of the method may comprise choosing one image, called reference image, among the respective top view images, estimating for each respective top view image a respective geometric deformation between the respective top view image and the reference image, computing by the respective geometric deformations respective subpixel positions of the respective top view images relative to one high-resolution coordinate system, interpolating at the respective subpixel positions to sample at least part of at least some of the respective top view images on a prescribed grid to obtain a high-resolution image.

Abstract: An image sensor, electronic device and method thereof that performs on-sensor single object class detection using an on-sensor single object class detection deep neural network (DNN), such as a face detection DNN. The single object class detection DNN includes a pixel array layer configured to capture an image and transfer image data of the captured image, and a logic and single object class detection deep neural network (DNN) layer that receives the image data directly from the pixel array layer and outputs the image data with the single object class detection data to a communication bus of an electronic device.

Abstract: A system, method, and apparatus for displaying a fused reconstructed image with a multidimensional image are disclosed. An example imaging system receives a selection corresponding to a portion of a displayed multidimensional visualization of a surgical site. At the selected portion of the multidimensional visualization, the imaging system displays a portion of a three-dimensional image which corresponds to the selected multidimensional visualization such that the displayed portion of the at least one of the three-dimensional image or model is fused with the displayed multidimensional visualization.

Abstract: A method comprising: receiving an image stream of a mammalian cardiac muscle cell; defining or having defined a region of interest (ROI) within said cell; calculating a fast Fourier transform (FFT) of said ROI; detecting peaks in said FFT; and determining at least one of sarcomere length, mitochondrial length, and mitochondrial width, based, at least in part, in said detected peaks.

Abstract: A method and apparatus for correcting aberrations over the entire field of view of an optical system, in which a first part of the apparatus applies different pre-compensating aberrations individually to different portions of the field of view, such that aberrations caused by a second part of the apparatus cancel the aberrations applied by the first part. The first part of the apparatus is temporally, angularly, or spatially multiplexed and the second part of the apparatus is spatially or angularly multiplexed such that ray bundles corresponding to subsets of contiguous pixels in an image source are each subjected to corresponding pre-compensating aberrations and subsequent aberrations, resulting in a substantially non-aberrated performance over the entire field of view of the optical system.

Abstract: A workpiece image search apparatus includes: a workpiece image deformation unit that generates a third workpiece image by deforming a second workpiece image so that a difference in workpiece shape between a first workpiece image and the second workpiece image becomes smaller, wherein the first workpiece image is obtained by projecting a first workpiece shape of a first workpiece on a two-dimensional plane, and the second workpiece image is obtained by projecting a second workpiece shape of a second workpiece on a two-dimensional plane; and a similarity calculation unit that calculates a similarity between the first workpiece shape and the second workpiece shape by comparing the third workpiece image with the first workpiece image.

Abstract: Provided is a state determination apparatus that appropriately performs pattern classification processing and/or pattern determination processing even when a map generated by the SOM technique includes discontinuous image regions. In the state determination apparatus, the matching processing unit obtains adaptability data indicating a correlation degree between template data indicating a state and the SOM output data. The state determination unit obtains a state evaluation value based on an activity value obtained by the activity value obtaining unit and the adaptability value. The time series estimation unit determines a state of an input data based on the state evaluation value and state transition probability between states. This allows for appropriately performing pattern classification processing and/or pattern determination processing even when a map generated by the SOM technique includes discontinuous image regions.

Abstract: A method of applying a confidence classifier for intent classification in association with an automated chat bot according to an embodiment includes processing, by a computing system, an utterance with an intent classifier to determine a probability distribution of possible intents associated with the utterance, generating, by the computing system, a plurality of measures of peakedness of the probability distribution, and applying, by the computing system, a trained confidence classifier to determine a single normalized probability of a most likely intent associated with the utterance based on the plurality of measures of peakedness of the probability distribution.

Abstract: Techniques for providing perceptually motivated video pre-filtering are described.

Abstract: Embodiments are disclosed for characterizing and quantifying composite laminate structures. The embodiments take a composite laminate of unknown ply stack composition and sequence and determine various information about the individual plies, such as ply stack, orientation, microstructure, and type. The embodiments can distinguish between weave types that may exhibit similar planar stiffness behaviors, but would produce different failure mechanisms. Individual ply information may then be used to derive the laminate bulk properties from externally provided constitutive properties of the fiber and matrix, including extensional stiffness, bending-extension coupling stiffness, bending stiffness, and the like. The laminate bulk properties may then be used to generate a probabilistic failure envelope for the composite laminate. In some embodiments, ply stack type and sequence may also be determined for a curved composite laminate using the disclosed embodiments by adding a rotational stage.

Abstract: In a method for deconvolving image data, image data of an object are captured with a number n of confocal beam paths. The image data are converted into resultant image data by means of a point spread function. The resultant image data are deconvolved again in the frequency domain using a deconvolution function, wherein the deconvolution function contains the formation of at least a number n of sum terms and a Wiener parameter w. The results of the sum terms are stored in retrievable fashion; the Wiener parameter W is modified at least once proceeding from its original value and the deconvolution is carried out by means of the deconvolution function with the modified Wiener parameter w and the stored results of the sum terms.

Abstract: Embodiments of a system and method for sorting and delivering articles in a processing facility based on image data are described. Image processing results such as rotation notation information may be included in or with an image to facilitate downstream processing such as when the routing information cannot be extracted from the image using an unattended system and the image is passed to an attended image processing system. The rotation notation information may be used to dynamically adjust the image before presenting the image via the attended image processing system.

Abstract: The technology disclosed relates to structured illumination microscopy (SIM). In particular, the technology disclosed relates to capturing and processing, in real time, numerous image tiles across a large image plane, dividing them into subtiles, efficiently processing the subtiles, and producing enhanced resolution images from the subtiles. The enhanced resolution images can be combined into enhanced images and can be used in subsequent analysis steps. The technology disclosed includes logic to reduce computing resources required to produce an enhanced resolution image from structured illumination of a target. A method is described for producing an enhanced resolution image from images of a target captured under structured illumination. This method applies one or more transformations to non-redundant data and then recovers redundant data from the non-redundant data after the transformations.

Abstract: An image processing method and apparatus are provided. The image processing apparatus includes a receiver configured to receive image data; and a processor configured to generate first data by performing a Fourier calculation on the received image data, generate second data by performing prism phase computation on the first data, generate third data by adding the first data and the second data, and perform encoding based on the third data.

Abstract: Provided is a method for reconstructing content image data. The method includes selecting a first point and a second point in a first image of first content, selecting a third point and a fourth point in a second image of second content (the second image is an image corresponding to the first image and the third point and the fourth point are points in an image corresponding to the first point and the second point, respectively), generating a first reference vector using the first point and the second point, generating a second reference vector using the third point and the fourth point, calculating a rotation, scale, and transformation (RST) value from the first image to the second image using the first reference vector and the second reference vector; and reconstructing the second content using the calculated RST value.

Abstract: Software instructions are executed on a processor within a computer system to configure a steaming engine with stream parameters to define a multidimensional array. The stream parameters define a size for each dimension of the multidimensional array and a pad value indicator. Data is fetched from a memory coupled to the streaming engine responsive to the stream parameters. A stream of vectors is formed for the multidimensional array responsive to the stream parameters from the data fetched from memory. A padded stream vector is formed that includes a specified pad value without accessing the pad value from system memory.

Abstract: A correlithm object processing system includes a reference table that stores a plurality of correlithm objects, and a first node communicatively coupled to a second node by a communication channel. The first node is configured to receive a particular one of the plurality of correlithm objects from the second node over the communication channel. The first node determines distances between the received correlithm object and each of the plurality of correlithm objects stored in the reference table. The first node further identifies one of the plurality of correlithm objects from the reference table with the shortest distance, and outputs the identified correlithm object.

Abstract: A computerized method of artifact regulation in deep model training for image transformation first performs one cycle of deep model training by computing means using a training data, a validation data, a similarity loss function, an artifact regulation loss function and a weight of loss functions to generate similarity loss and artifact regulation loss and a deep model. The method then performs a training evaluation using the similarity loss and the artifact regulation loss thus obtained to generate a training readiness output. Then, depending upon the training readiness output, the method may be terminated if certain termination criteria are met, or may perform another cycle of deep model training and training evaluation, with or without updating the weight, until the termination criteria are met. Alternatively, the deep model training in the method may be a deep adversarial model training or a bi-directional deep adversarial training.

Abstract: A receiver, method, terminal device, visible light transmissive structure and system for decoding light signals and light signals received in an area of overlap of light rays emanating from different lighting devices, each transmitting unique ID data. Light rays (45, 46, 47) entering the receiver (39) are optically spread apart in longitudinal direction (x) of an array of photodetectors (21). The thus spread light rays (45a, 46a, 47a) are optically diverged and spread further over the radiant active surface (29) of a particular photodetector (22-28), thereby optimizing the amount of light received at a respective photodetector (22-28).

Abstract: Provided is a charged particle beam device to enable determination of a noise source of a charged particle beam device that can cause a noise frequency component superimposed on a measurement image. The charged particle beam device includes a unit that extracts information regarding a noise source.

Abstract: A method and apparatus for converting first image data corresponding to a first depth and second image data corresponding to a second depth may be used for displaying a 3D image represented by the first image data and the second image data and performing FFT on the converted first image data and the converted second image data.

Abstract: A computer that includes a processor and memory that stores processor-executable instructions. The processor can be programmed to: generate a plurality of transform patch images (PTPIs) by applying a mathematical transform operator to a plurality of map-perspective patch images (PMPPIs) received from at least one vehicle laser-scanner; combine at least some of the PTPIs into a single patch image; and construct a map patch image using the single patch image.

Abstract: Embodiments are disclosed for providing a machine-generated response (e.g., answer) to an input (e.g., question) based on long-term memory information. A method according to some embodiments include receiving an input; converting the input into an input feature vector in an internal feature representation space; updating a memory data structure by incorporating the input feature vector into the memory data structure; generating an output feature vector in the internal feature representation space, based on the updated memory data structure and the input feature vector; converting the output feature vector into an output object; and providing an output based on the output object as a response to the input.

Abstract: A system and method for generating a camouflage by integrating the phase data of a Turing pattern, containing data at multiple levels of scale, with Fourier frequency data corresponding to that of the environment(s) in which the camouflage is to be employed.

Abstract: Imager arrays, array camera modules, and array cameras in accordance with embodiments of the invention utilize pixel apertures to control the amount of aliasing present in captured images of a scene. One embodiment includes a plurality of focal planes, control circuitry configured to control the capture of image information by the pixels within the focal planes, and sampling circuitry configured to convert pixel outputs into digital pixel data. In addition, the pixels in the plurality of focal planes include a pixel stack including a microlens and an active area, where light incident on the surface of the microlens is focused onto the active area by the microlens and the active area samples the incident light to capture image information, and the pixel stack defines a pixel area and includes a pixel aperture, where the size of the pixel apertures is smaller than the pixel area.

Abstract: The method according to the invention for the correction of measurement data acquired along Cartesian lines in k-space, which measurement data have been acquired by means of a pulse sequence in which gradients are switched simultaneously during the radiation of at least one non-selective excitation pulse, includes the steps of measurement data acquired with the pulse sequence are entered into k-space, i.e. entered into a memory organized as k-space, a pulse excitation profile is determined, and the acquired measurement data are corrected using the pulse excitation profile, the correction including a de-convolution operation in at least one of the three k-space directions. The correction of measurement data according to the invention allows an unrestricted use of pulse sequences, in particular gradient echo sequences, in which an excitation is implemented given already activated gradients (for example for noise reduction).

Abstract: In one embodiment, a method of amplifying temporal variation in at least two images comprises examining pixel values of the at least two images. The temporal variation of the pixel values between the at least two images can be below a particular threshold. The method can further include applying signal processing to the pixel values.

Abstract: In one embodiment, a method of amplifying temporal variation in at least two images includes converting two or more images to a transform representation. The method further includes, for each spatial position within the two or more images, examining a plurality of coefficient values. The method additionally includes calculating a first vector based on the plurality of coefficient values. The first vector can represent change from a first image to a second image of the at least two images describing deformation. The method also includes modifying the first vector to create a second vector. The method further includes calculating a second plurality of coefficients based on the second vector.

Abstract: Useful and meaningful machine characteristic information may be derived through analysis of oversampled digital data collected using dynamic signal analyzers, such as vibration analyzers. Such data have generally been discarded in prior art systems. In addition to peak values and decimated values, other oversampled values are used that are associated with characteristics of the machine being monitored and the sensors and circuits that gather the data. This provides more useful information than has previously been derived from oversampled data within a sampling interval.

Abstract: The present disclosure relates to a method and terminal device for processing an image. The method includes: acquiring face information from a template image, if receiving a request for processing an image containing a face; and applying a photo makeover on the face according to the face information acquired from the template image. By acquiring face information from a template image and automatically applying a photo makeover on the face according to the face information acquired from the template image, manual setting for makeover parameters will be avoided and the efficiency will be improved.

Abstract: Example embodiments disclose a method of generating a feature vector, a method of generating a histogram, a learning unit classifier, a recognition apparatus, and a detection apparatus, in which a feature point is detected from an input image based on a dominant direction analysis of a gradient distribution, and a feature vector corresponding to the detected feature point is generated.

Abstract: According to the present invention, an imaging condition setting method includes an object discriminating step S1-1 of discriminating the object by using images, a discriminable range generating step S1-2 of generating a discriminable range that is a range of the imaging conditions under which the object is discriminable, an identification determination result range generating step S1-2 of generating an identification determination result range that is a range of the imaging conditions under which the objects are determined as identical, an imaging condition setting rule generating step S1-4 of generating an imaging condition setting rule that is a rule for changing an imaging condition by using the discriminable range and the identification determination result range, and an imaging condition setting step S2-4 of setting an imaging condition under which the object is discriminable by using the imaging condition setting rule generated by the imaging condition setting rule generating step.

Abstract: Techniques for presenting insight into classification trees may include performing a grouping analysis to group leaf nodes of a classification tree into a significant group and an insignificant group, performing influential target category analysis to identify one or more influential target categories for the leaf nodes of the classification tree in the significant group, and presenting one or more insights into the classification tree based on the grouping analysis and the influential target category analysis. Techniques for presenting insight into regression trees may include performing a grouping analysis to group leaf nodes of a regression tree into a high group and a low group, performing unusual node detection analysis to detect one or more outlier nodes in the high group and in the low group, and presenting one or more insights into the regression tree based on the grouping analysis and the unusual node detection analysis.

Abstract: A system and method for registering range images from objects detected by multiple LiDAR sensors on a vehicle. The method includes aligning frames of data from at least two LiDAR sensors having over-lapping field-of-views in a sensor signal fusion operation so as to track objects detected by the sensors. The method defines a transformation value for at least one of the LiDAR sensors that identifies an orientation angle and position of the sensor and provides target scan points from the objects detected by the sensors where the target scan points for each sensor provide a separate target point map. The method projects the target point map from the at least one sensor to another one of the LiDAR sensors using a current transformation value to overlap the target scan points from the sensors.

Abstract: In one embodiment, a method of amplifying temporal variation in at least two images includes converting two or more images to a transform representation. The method further includes, for each spatial position within the two or more images, examining a plurality of coefficient values. The method additionally includes calculating a first vector based on the plurality of coefficient values. The first vector can represent change from a first image to a second image of the at least two images describing deformation. The method also includes modifying the first vector to create a second vector. The method further includes calculating a second plurality of coefficients based on the second vector.