Abstract: An image processing apparatus includes a memory configured to store first region detection information of a first frame; and a processor. The processor is configured to: identify a first pixel region corresponding to the first region detection information from a second frame, perform region growing processing on the first pixel region based on an adjacent pixel region that is adjacent to the first pixel region, obtain second region detection information of the second frame, based on the region growing processing, and perform image processing on the second frame based on the second region detection information.

Abstract: A method of generating and optimizing a codebooks for document analysis comprises: receiving a first set of document images; extracting a plurality of keypoint regions from each document image of the first set of document images; calculating local descriptors for each keypoint region of the extracted keypoint regions; clustering the local descriptors such that each center of a cluster of local descriptors corresponds to a respective visual word; generating a codebook containing a set of visual words; and optimizing the codebook by maximizing mutual information (MI) between a target field of a second set of document images and at least one visual word of the set of visual words.

Abstract: An industrialized system and method for rice grain recognition. An optical image is taken and transmitted to a digital platform, wherein the system segments the optical image and extracts and/or measures appropriate grain features from the image describing different aspects of the grain. The image is processed by the system which includes a selector selecting different machine learning structures, applying the different machine learning structures to the extracted features for rice grain recognition, and selecting the best of the applied machine learning structures by a random sampling process. The selected best of the applied machine learning structures is further optimized by varying an appropriate threshold by a threshold trigger based on a confusion matrix comprising. An active learning structure based on the confusion matrix to the user. The system is retrained based on the feedback parameters of the feedback loop.

Abstract: The invention provides an image segmentation method and an electronic device. The image segmentation method includes the following steps. Regression analysis is performed on a first gray-scale image to obtain a residual image having an object backbone area. A pixel value of each pixel in the object backbone area is defined as an average gray-scale value of the object backbone area in the residual image, and a second gray-scale image having the object backbone area is generated. It is recursively determined whether a residual polarity of each adjacent pixel adjacent to edge pixels of the object backbone area in the residual image is the same as a residual polarity of the corresponding edge pixel, and whether a pixel value of each adjacent pixel is greater than a first threshold, so as to expand the object backbone area in the second gray-scale image, which is extracted as a target object.

Abstract: An example image feature extraction system comprises an encoder neural network having a first set of layers and a decoder neural network having a second set of layers and a third set of layers. The encoder neural network receives an input image, processes the input image through the first set of layers, and computes an encoded feature map based on the input image. The decoder neural network receives the encoded feature map, processes the encoded feature map through the second set of layers to compute a keypoint score map, and processes the encoded feature map through at least a portion of the third set of layers to compute a feature description map.

Abstract: Vehicle alert and control systems and methods taking into account a detected road friction at a following vehicle and a predicted road friction by the following vehicle. The detected road friction between the following vehicle tires and the road surface may be assessed using a variety of methodologies and is used to compute a critical safety distance between the following vehicle and the preceding vehicle and a critical safety speed of the following vehicle. The predicted road friction ahead of the following vehicle may also be assessed using a variety of methodologies (lidar, camera, and cloud-based examples are provided) and is used to compute a warning safety distance between the following vehicle and the preceding vehicle and a warning safety speed of the following vehicle. These functionalities may be applied to vehicle/stationary object warning and response scenarios as well.

Abstract: The invention relates to a method for classifying spectra of objects having complex information content after recording of the spectra involving the use of a method for preprocessing data and of a method, associated with the data preprocessing, for classification with the calculation of a classifier. After the recording of the spectra and the preprocessing of the spectra, a multiple classification method is thereby performed with at least two different methods for the data preprocessing of the spectra and the method, assigned to the respective data preprocessing, for classification.

Abstract: An automatically detecting method for time-varying text region of interest is disclosed. The automatically detecting method is adapted to an image processing unit of an information retrieval system, to detect a time-varying text region of interest having specific characters or character set as unit on an operation screen of a manufacturing machine, a processing machine or other equipment; furthermore, the automatically detecting method can be performed based on presence or absence of the historical screen data, and union of the detected region proposals for the time-varying text region of interest, to obtain an automatically labeled and selected time-varying text region of interest. According to the automatically detecting method, the user only needs to confirm whether the required data are labeled and selected, so it is more convenient for the user to setting data, and greatly helpful to reduce the setting time and correctly detect the required information.

Abstract: An image collection chip, an object imaging recognition device and an object imaging recognition method are provided. The image collection chip comprises an optical modulation layer and an image sensing layer. The optical modulation layer is located on the image sensing layer. The optical modulation layer is provided with at least two modulation units and the image sensing layer is provided with sensing units corresponding to the at least two modulation units in a form of up and down. Each of the at least two modulation units is provided with at least one modulation subunit. Two or more modulation units among the at least two modulation units have different graphic structures, and the two or more modulation units having different graphic structures have different modulation roles on spectrum.

Abstract: Described examples relate to an apparatus comprising a memory for storing a sequence of image frames and at least one processor. The at least one processor may be configured to receive a first image frame of a sequence of image frames from an image capture device and select a first portion of a first image frame. The at least one processor may also be configured to obtain alignment information and determine a first portion and a second portion of a second image frame based on the alignment information. Further, the at least one processor may be configured to determine a bounding region within the second image frame and fetch image data corresponding to the bounding region of the second image frame from memory. In some examples, the first image frame may comprise a base image and the second image frame may comprise an alternative image frame. Further, the first image frame may comprise any one of the image frames of the sequence of image frames.

Abstract: According to one embodiment, an image processing device includes first storage and a processor. The first storage is configured to store a first statistical model generated by learning bokeh which occurs in a first image. The processor is configured to acquire a second image, acquire a bokeh value which indicates bokeh occurring in the second image and an uncertainty level which indicates a level of uncertainty for the bokeh value, generate a first bokeh map based on the bokeh value and uncertainty level, and acquire a second bokeh map obtained by interpolating a bokeh value with respect to the first bokeh map. The bokeh value and the uncertainty level are output from the first statistical model by inputting the second image into the first statistical model.

Abstract: A method for classifying a vasculature comprises training a training device with an initial model of a vasculature using diagnostic image data representing a geometry for a plurality of vessels of a vessel tree and including a respective vessel labeling for each vessel, providing at least one diagnostic image of a patient's vessel tree and identifying a variation between the vessel tree represented by the initial model and the patients vessel tree. This variation is checked and labeled in order to improve the trained model. The process may be repeated iteratively until reaching an accurate patient-specific model of the vasculature.

Abstract: A solution to identify the layout elements in a document is provided. The documents are formulated in an integrated visual space, where they are treated uniformly as a rasterized image. The transformation to image space facilitates exploitation of a spectrum of stylistic cues, such as spacing between the lines and paragraphs. Effective recognition of layout elements is provided by applying a synthetic generator model that creates artificial documents with the required labels and bounding boxes. The generator model is based on a Bayesian Network, offers full flexibility in controlling the document types and labels, and can introduce artificial defects to synthesize low-quality documents. An artificial intelligence model for detecting layouts is trained based on these synthetic documents and the resultant model is used to identify the layout elements in real-world documents. The resulting layout elements, when augmented with the text content, greatly aids in effective information retrieval.

Abstract: In variants, the method can include: sampling cavity measurements of the cook cavity; determining an image representation using the cavity measurements; determining a food class based on the image representation; optionally comparing the image representation to prior image representations; optionally determining a new food class based on the image representation; optionally updating a food identification module with the new food class; and optionally determining a cook program associated with the new food class.

Abstract: A semantic segmentation method for aircraft point cloud based on voxelization and three views, including: filtering a collected point cloud followed by centralization to obtain a centralized point cloud; inputting the centralized point cloud into a T-Net rotation matrix network; rotating the centralized point cloud to a front side followed by voxelization to obtain a voxelized point cloud; subjecting the voxelized point cloud to voxel filling to obtain a voxel-filled point cloud; calculating thickness maps of three views of the voxel-filled point cloud, followed by sequentially stitching and inputting to the point cloud semantic segmentation network to train the point cloud semantic segmentation network; inputting the collected point cloud into the trained point cloud semantic segmentation network; and predicting a result semantic segmentation of a 3D point cloud of the aircraft.

Abstract: Aspects of the invention provide a method of face recognition that includes receiving plural frames of a video stream imaging a candidate individual, e.g., in the field of view of a camera, and generating for each of those frames a score of the image and/or of the candidate therein. This can include a score (or count) indicative of the number of individuals present in the frame, a pose of the candidate individual (e.g., face-on or otherwise), blur in the image, and so forth. The method further includes selecting, based on the respective scores of the frames, a subset of the frames for matching by a face recognizer against a set of one or more images of designated individuals. That set may be of individuals approved for access, individuals to be prevented for access, or otherwise. An output can be generated based on such matching by the face recognizer.

Abstract: The present application provides a computer-implemented method for generating a digital data set representing a target tooth arrangement, comprising: obtaining a first and a second 3D digital models respectively representing upper jaw teeth and lower jaw teeth under an initial tooth arrangement, where the first and the second 3D digital models are in a predetermined relative positional relationship; extracting a tooth level feature vector from each tooth of the first and second 3D digital models; preliminarily aligning the first and second 3D digital models based on the tooth level feature vectors using a trained first deep neural network; extracting a jaw level feature vector for each tooth of the preliminarily aligned first and second 3D digital models; and further aligning the preliminarily aligned first and second 3D digital models to obtain a target tooth arrangement based on the jaw level feature vectors using a trained second deep neural network.

Abstract: A pulsed light communication device has a plurality of indicator light emitting diodes emitting diodes emitting at least one of a plurality of wavelengths of colored light to correspond to a designated color assigned to a security level for a network. A continuous uninterrupted modulated pulsed light emitting diode light signal may be generated having a sensitivity threshold detection level exceeding minimal parameters of a photodetector.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating, transmitting, directing, receiving, and processing optical subcarriers. In some implementations, a system includes a Tier 1 switch that supplies a plurality of data channels; a transmitter that receives the plurality of data channels, the transmitter including an optical modulator that supplies a plurality of optical subcarriers based on the plurality of data channels; an optical platform that receives the plurality of optical subcarriers, the optical platform having a plurality of outputs, each of which supplying at least one of the plurality of subcarriers; a plurality of receivers, each receiving one or more of the plurality of optical subcarriers and supplying one or more of the plurality of data channels; and a plurality of servers, each of which receiving one or more of the plurality of data channels.

Abstract: Embodiments are disclosed for health assessment and diagnosis implemented in an artificial intelligence (AI) system. The AI system takes as input information from a multitude of sensors measuring different biomarkers in a continuous or intermittent fashion. The proposed techniques disclosed herein address the unique challenges encountered in implementing such an AI system.