Abstract: Embodiments relate to circuitry for temporal processing and image fusion. An image fusion circuit receives captured images, and generates corresponding image pyramids. The generated image pyramids are raster or tiled processed, and stored in memory. A fusion module receives a first and second image pyramids from the memory, warps the first image pyramid based upon the second image pyramid, and fuses the warped first image pyramid with the second image pyramid to generate a fused image pyramid, which may be used for further processing, and may also be stored back into the memory. Because pyramid generation occurs prior to warping and fusion, and by allowing fused image pyramids to be stored back into memory, the image fusion circuitry is configurable to implement a variety of temporal processing functions involving different image fusion combinations.

Abstract: A system for performing remote artificial intelligence-assisted electronic warranty verification including at least one processor configured to transmit an instruction to capture at least one product image of a specific product, receive and perform product image analysis on the product image to identify at least one product-distinguishing characteristic, transmit an instruction to capture an image of a purchase receipt, receive and perform receipt image analysis on the purchase receipt image to identify product purchase information, access a universal data structure containing data on products offered by suppliers, use the at least one product-distinguishing characteristic and product purchase information to identify in the universal data structure the specific product, identify in the universal data structure a link to a warranty data structure of the supplier, access the link to lookup the specific product and receive a warranty coverage indication from the supplier data structure, and transmit an indicatio

Abstract: A preoperative survival prediction method and a computing device applying the method include constructing a data seta according to a plurality of enhanced medical images and a resection margin of each enhanced medical image and obtaining a plurality of training data sets from the constructed data set. For each training data set, multi-task prediction models are trained. A target multi-task prediction model is selected from the plurality, and a resection margin prediction value and a survival risk prediction value are obtained by predicting an enhanced medical image to be measured through the target multi-task prediction model. The multi-task prediction model more effectively captures the changes over time of the tumor in multiple stages, so as to enable a joint prediction of a resection margin prediction value and a survival risk prediction value.

Abstract: A system and method for facilitating DBS electrode trajectory planning using a machine learning (ML)-based feature identification scheme configured to identify and distinguish between various regions of interest (ROIs) and regions of avoidance (ROAs) in a patient's brain scan image. In one arrangement, standard orientation image slices as well as re-sliced images in non-standard orientations are provided in a labeled input dataset for training a CNN/ANN for distinguishing between ROIs and ROAs. Upon identification of the ROIs and ROAs in the patient's brain scan image, an optimal trajectory for implanting a DBS lead may be determined relative to a particular ROI while avoiding any ROAs.

Abstract: Controls within images of a user interface of a computer application are detected by way of region-based R-FCN and Faster R-CNN engines. Datasets comprising images containing application control, wherein the application controls include images of application where width is greater than height, width is equal to height and height is greater than width are retrieved. Each of the datasets is processed with the R-FCN and Faster R-CNN engines to generate a software configured to recognize, from an input image, application controls wherein the application controls are characterized by dimensions where width is greater than height, where width is substantially equal to height, and where height is greater than width.

Abstract: A method of pipelining inference of a neural network, which includes an i-th layer (i being an integer greater than zero) and an (i+1)-th layer, includes processing, for a first input image, first i-th values of the i-th layer to generate first (i+1)-th values for the (i+1)-th layer, processing, for the first input image, the first (i+1)-th values of the (i+1)-th layer to generate output values, and concurrently with processing, for the first image, the (i+1)-th values, processing, for a second input image, second i-th values of the i-th layer to generate second (i+1)-th values.

Abstract: A non-transitory computer-readable recording medium storing a training data generation program for causing a computer to execute processing including: identifying, from among meta-analysis literatures stored in a memory, a plurality of meta-analysis literatures in which a first literature is cited; determining a degree of similarity between the plurality of identified meta-analysis literatures based on feature information of the plurality of identified meta-analysis literatures; and in response to the degree of similarity being equal to or higher than a threshold, generating training data for machine learning including the first literature.

Abstract: A method for generating simulated point cloud data, a device, and a storage medium includes: acquiring at least one frame of point cloud data collected by a road collecting device in an actual environment without a dynamic obstacle as static scene point cloud data; setting, least one dynamic obstacle in a coordinate system matching the static scene point cloud data; simulating in the coordinate system, a plurality of simulated scanning lights emitted by a virtual scanner located at an origin of the coordinate system; updating the static scene point cloud data according to intersections of the plurality of simulated scanning lights and the at least one dynamic obstacle to obtain the simulated point cloud data comprising point cloud data of the dynamic obstacle; and at least one of adding a set noise to the simulated point cloud data, and, deleting point cloud data corresponding to the dynamic obstacle according to a set ratio.

Abstract: Various embodiments are described that relate to classification of an unknown object. A time series signal associated with an unknown object can be obtained from a sensor. The time series signal can be subjected to a transform set, such as a Fourier transform and a discrete cosine transform, to produce a transform outcome. Based, at least in part, on the transform outcome, the unknown object can be classified.

Abstract: The disclosure relates to methods and systems for detecting the orientation of an oocyte and its polar body. Examples include an automated method for detection of an orientation of an oocyte, the method including: i) acquiring an image of the oocyte; ii) defining first and second elliptical features in the image based on edges detected in the image; iii) calculating an orientation of the second elliptical feature relative to the first elliptical feature; and iv) outputting a relative orientation of a polar body of the oocyte based on the orientation of the second elliptical feature relative to the first elliptical feature.

Abstract: An embodiment may involve obtaining an image composed of color channels, wherein each of the color channels represents colors therein with n bits per pixel; quantizing each of the color channels to be represented by m bits per pixel; using a space-filling curve to convert each of the color channels as quantized into respective vectors; generating, for each of the respective vectors, a respective set of m arrays, wherein the m arrays for a particular vector of the respective vectors contain indices of where a fixed value selected from a range of 0 to m?1 is found in the particular vector; applying, to each of the m arrays for each of the respective vectors, differential encoding and compression of the indices therein; mapping each of the m arrays for each of the respective vectors to blocks of nucleotides; synthesizing the blocks; and storing, in a DNA-based storage medium, the blocks.

Abstract: Certain aspects involve video inpainting in which content is propagated from a user-provided reference frame to other video frames depicting a scene. For example, a computing system accesses a set of video frames with annotations identifying a target region to be modified. The computing system determines a motion of the target region's boundary across the set of video frames, and also interpolates pixel motion within the target region across the set of video frames. The computing system also inserts, responsive to user input, a reference frame into the set of video frames. The reference frame can include reference color data from a user-specified modification to the target region. The computing system can use the reference color data and the interpolated motion to update color data in the target region across set of video frames.

Abstract: This disclosure relates to a method and system for identifying products using digital fingerprints. The method includes receiving, by a product tracking system, a set of images corresponding to a product, wherein the set of images are received along with associated context information. The method generates a set of standardized images by pre-processing the set of images. Each standardized image of the set of standardized images are further segmented into a plurality of zones. A zone wise fingerprint is generated for each zone of the plurality of zones. A product digital fingerprint is generated for the product by combining zone wise fingerprints associated with the set of standardized images, wherein the product digital fingerprint identifies the product.

Abstract: A processor may receive an image and determine a number of foreground pixels in the image. The processor may obtain a result of optical character recognition (OCR) processing performed on the image. The processor may identify at least one bounding box surrounding at least one portion of text in the result and overlay the at least one bounding box on the image to form a masked image. The processor may determine a number of foreground pixels in the masked image and a decrease in the number of foreground pixels in the masked image relative to the number of foreground pixels in the image. Based on the decrease, the processor may modify an aspect of the OCR processing for subsequent image processing.

Abstract: A colon polyp image processing method is provided. A value of a blood vessel color feature in an endoscopic image is classified by using an image classification model trained using a neural network algorithm to determine that the endoscopic image is a white light type picture or an endoscope narrow band imaging (NBI) type picture. A polyp in the endoscopic image is detected by using a polyp positioning model based on the determination that the endoscopic image is the white light type picture or the NBI type picture. A polyp type classification detection is performed on the detected polyp in the endoscopic image by using a polyp property identification model, and outputting an identification result.

Abstract: An apparatus for chemical mechanical polishing includes a platen having a surface to support a polishing pad, a carrier head to hold a substrate against a polishing surface of the polishing pad, a pad conditioner to press an abrasive body against the polishing surface, an in-situ polishing pad monitoring system including an imager disposed above the platen to capture an image of the polishing pad, and a controller configured to receive the image from the monitoring system and generate a measure of polishing pad surface roughness based on the image. The controller can use machine-learning based image processing to generate the measure of surface roughness.

Abstract: A computer readable recording medium storing at least one program, wherein an image quality improvement method is performed when the program is executed. The image quality improvement method comprising: (a) classifying data units of a target image to normal data units and abnormal data units based on relations between brightness values of the data units and a classification parameter, wherein the classification parameter is related with an image quality of the target image or the brightness values of the data units; and (b) adjusting the brightness values of the abnormal data units based on an adjusting parameter to generate adjusted brightness values, such that differences between the adjusted brightness values and the brightness values of the normal data units are reduced. An optical navigation method using the image quality improvement method is also disclosed.

Abstract: Methods are provided to project depth-spanning stacks of limited depth-of-field images of a sample into a single image of the sample that can provide in-focus image information about three-dimensional contents of the image. These methods include applying filters to the stacks of images in order to identify pixels within each image that have been captured in focus. These in-focus pixels are then combined to provide the single image of the sample. Filtering of such image stacks can also allow for the determination of depth maps or other geometric information about contents of the sample. Such depth information can also be used to inform segmentation of images of the sample, e.g., by further dividing identified regions that correspond to the contents of the sample at multiple different depths.

Abstract: Segmentation of an image into individual body parts is performed based on a trained model. The model is trained with a plurality of training images, each training image representing a corresponding training figure. The model is also trained with a corresponding plurality of segmentations of the training figures. Each segmentation is generated by positioning body parts between defined positions of joints of the represented figure. The body parts are represented by body part templates obtained from a template library, with the templates defining characteristics of body parts represented by the templates.

Abstract: There is provided an information processing apparatus including a processing unit that tracks a target on the basis of a captured image that has been captured by an imaging device and sensor information obtained by communication from a sensor that senses the target.