Abstract: An information processing system includes an image reading device and an information processing device. The image reading device reads a document to generate target image data. The information processing device processes the target image data. The information processing device includes a first conversion processing section, a second conversion processing section, and a selection section. The first conversion processing section is capable of converting image data to character code data. The second conversion processing section is capable of converting image data to character code data. The selection section selects conversion of the target image data to character code data by the first conversion processing section or the second conversion processing section.

Abstract: A system and a method for on-line analysis of a structure of dried shredded tobacco are provided. The system includes a shredded tobacco structure on-line analysis module, a shredded tobacco filling capacity prediction model module, and an early-warning module. The shredded tobacco structure on-line analysis module includes a sample extraction unit, a sample analysis unit and a shredded tobacco filling capacity data acquisition unit. The shredded tobacco filling capacity prediction model module includes a model parameter screening unit and a model construction unit. An early-warning threshold is provided in the early-warning module, and when a deviation of a predicted shredded tobacco filling capacity from a standard value exceeds the early-warning threshold, an alarm is given. The new system is an intelligent system with functions of shredded tobacco structure analysis, shredded tobacco filling capacity prediction, and abnormality early-warning determination and analysis.

Abstract: The present disclosure a system and method for generating a tomographic image of a subject. In some aspects, the method includes receiving an initial image acquired from a subject using the tomographic imaging system, and performing, using the initial image and a cost function model, a penalty calculation based on a spatially variant hyper-parameter. The method also includes generating an updated image using the penalty calculation, and generating a finalized image by iteratively updating the updated image until a stopping criterion is met.

Abstract: A method for performing computer-aided diagnosis (CAD) based on a medical scan image includes: pre-processing the medical scan image to produce an input image, a flipped image, and a spatial alignment transformation corresponding to the input image and the flipped image; performing Siamese encoding on the input image to produce an encoded input feature map; performing Siamese encoding on the flipped image to produce an encoded flipped feature map; performing a feature alignment using the spatial alignment transformation on the encoded flipped feature map to produce an encoded symmetric feature map; and processing the encoded input feature map and the encoded symmetric feature map to generate a diagnostic result indicating presence and locations of anatomical abnormalities in the medical scan image.

Abstract: Provided is a method and apparatus for detecting a vanishing point in a driving image of a vehicle. The method includes: receiving the driving image; generating a probability map, comprising probability information about a position of the vanishing point in the driving image, from the driving image; detecting a vanishing point on the driving image by applying smoothing regression, which softens a boundary region of the vanishing point, to the probability map; and processing a task for driving the vehicle by converting an orientation of the driving image based on the vanishing point.

Abstract: An object identification method and an object identification device, the object identification method comprises: capturing color images and depth images that are aligned; performing motion detection on the captured color images and depth images to acquire a motion start frame and a motion end frame; comparing the motion end frame with the motion start frame in the color images to acquire a set of motion pixels; performing connected component analysis on the acquired set of motion pixels to obtain at least one connected component; and identifying an object in the at least one connected component.

Abstract: In one example embodiment, a computer-implemented method includes obtaining sensor data from a sensor, the sensor data corresponding to an image frame, and the sensor data including a first portion that corresponds to a portion of the image frame. The method includes pipelining the first portion of the sensor data into a machine-learned model before the sensor data corresponding to the entire image frame is transferred from the sensor to a memory device, to perform one or more inference operations on the first portion of the sensor data. The method includes generating as an output of the machine-learned model, in response to pipelining the sensor data corresponding to each portion of the image frame into the machine-learned model, a detection or classification of the one or more objects indicated within the sensor data.

Abstract: In a learning device, method, and program for a discriminator, and a discriminator, it is possible to enable accurate learning of a discriminator that discriminates a state of an object to be observed, such as a cell. An image acquisition unit acquires a first image including an influence of a meniscus and a second image with the influence of the meniscus eliminated for the same object to be observed. Next, a training data generation unit generates training data for learning a discriminator based on the second image. Then, a learning unit learns the discriminator based on the first image and the training data.

Abstract: A biological-information detection device includes a video input section accepting video signals including three wavelength components in an infrared region of reflected light from an object, a wavelength detecting section acquiring a wavelength and an intensity of the reflected light from the video signals, a face feature amount detecting section detecting a plurality of feature points of a face based on the video signals, a measurement target area identifying section identifying a measurement target area on a basis of the plurality of feature points of the face detected, a wavelength fluctuation detecting section detecting a difference between a wavelength of reflected light from the measurement target area at a certain point in time and a wavelength of reflected light at a point in time preceding the certain point in time, and a pulse wave detecting section detecting a change in the detected difference according to the point in time.

Abstract: An image processing apparatus generates a first image by adjusting luminance so as to preserve a signal value on a high-luminance side among signal values acquired by reading a document by a scanner, and detects a position of a region corresponding to the document in the generated first image. The image processing apparatus further generates a second image by performing adjustment so as to increase luminance of a pixel contained in the first image, and crops a document image from the generated second image based on the detected position of the region corresponding to the document.

Abstract: A set of images is received. A thermal anomaly is detected in the received set of images. The detected thermal anomaly is classified. Examples of classifications of thermal anomalies include: stationary targets, gas flares, agricultural anomalies, and wildfires. An action is taken based at least in part on the classified detected anomaly.

Abstract: A defect inspection system is disclosed. According to certain embodiments, the system includes a memory storing instructions implemented as a plurality of modules. Each of the plurality of modules is configured to detect defects having a different property. The system also includes a controller configured to cause the computer system to: receive inspection data representing an image of a wafer; input the inspection data to a first module of the plurality of modules, the first module outputs a first set of points of interests (POIs) having a first property; input the first set of POIs to a second module of the plurality of modules, the second module output a second set of POIs having the second property; and report that the second set of POIs as defects having both the first property and the second property.

Abstract: The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

Abstract: An image processing method acquires an image, restores a saturated region in which a pixel in the image has a first reference value based on a first illuminance component of the image, enhances a dark region in which a value of a pixel in the image is less than a second reference value based on the restored saturated region and the first illuminance component, and outputs a dark region-enhanced image.

Abstract: A face recognition system and a method for enhancing face recognition are provided. The method includes: receiving a face image and obtaining a feature of the face image from a feature extraction model; registering the face image to set the feature of the face image as a first recognition feature; performing a synthesis operation on the face image according to at least one first adjustment parameter to generate a synthetic image, and obtaining a feature of the synthetic image from the feature extraction model; comparing first recognition feature with the feature of the synthetic image to obtain a feature similarity; comparing the feature similarity with a threshold value to obtain a comparison result; and registering the synthetic image when the comparison result indicates that the feature similarity is less than or equal to the threshold value.

Abstract: Disclosed herein are ratiometric fluorescence imaging reagents, and image processing methods for using fluorescence ratio and intensity thresholds to detect and visualize regions of biological activity in biological specimens with improved accuracy.

Abstract: Improved targeting of cranial therapy is provided by warping a general purpose brain atlas to a measured head shape of the patient. The resulting patient-specific transformation from brain atlas to patient's head allows one to estimate the location of brain features of the patient without any patient specific brain imaging. Such cost-effective targeting of brain features is especially useful for therapies like transcranial magnetic stimulation, where accuracy of targeting brain structures and session-to-session consistency are both important.

Abstract: In a method of extracting features from an image, a plurality of initial key points are estimated based on an input image. A plurality of descriptors are generated based on a downscaled image that is generated by downscaling the input image. A plurality of feature points are obtained by matching the plurality of initial key points with the plurality of descriptors, respectively.

Abstract: Systems and methods for identity authentication based on liveness-verified biometric data that cannot be stolen/spoofed. In various embodiments, the disclosed systems and methods facilitate access to SaaS platforms, transactions, and/or physical assets via identity authentication based on comparison of liveness-verified biometric data (e.g., data that has been verified as derived from the correct actual live individual to avoid bad actors spoofing the data to gain access—in one embodiment, as one factor in a two factor authentication schema) to pre-verified identity data. Liveness-verified biometric data may, in various embodiments, be derived from facial features, fingerprints, voice recognition, DNA, etc. Generally, if the liveness and identity of the requesting individual cannot be verified, then the individual will not be permitted access.

Abstract: A biological-information detection device includes a video input section accepting video signals including three wavelength components in an infrared region of reflected light from an object, a wavelength detecting section acquiring a wavelength and an intensity of the reflected light from the video signals, a face feature amount detecting section detecting a plurality of feature points of a face based on the video signals, a measurement target area identifying section identifying a measurement target area on a basis of the plurality of feature points of the face detected, a wavelength fluctuation detecting section detecting a difference between a wavelength of reflected light from the measurement target area at a certain point in time and a wavelength of reflected light at a point in time preceding the certain point in time, and a pulse wave detecting section detecting a change in the detected difference according to the point in time.