Abstract: Methods, apparatus, and processor-readable storage media for automatically classifying images for storage-related determinations using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining at least one image associated with an enterprise; classifying one or more portions of the at least one image into one or more enterprise-related categories by processing at least a portion of the at least one image using one or more artificial intelligence techniques; and performing, based at least in part on the classifying of the one or more portions of the at least one image, one or more automated actions pertaining to storing the at least one image in at least one of multiple storage options.

Abstract: An information processing device obtains each piece of image data captured within a period of time from entering until exiting of a person at a store. The information processing device identifies joint positions of a skeleton related to the person by analyzing each piece of the image data. The information processing device identifies, as an action which indicates a degree of interest of the person in the product, an action performed by the person to a product in the store from the entering until the exiting, on a basis of the joint positions of the skeleton. The information processing device generates a detection rule that correlates the identified action and the product with each other.

Abstract: A method may include generating views materializing tensors generated by a convolutional neural network operating on an image. Determining the outputs of the convolutional neural network operating on the image with a patch occluding various portions of the image. The outputs being determined by generating queries on the views that performs, based at least on the changes associated with occluding different portions of the image, partial re-computations of the views. A heatmap may be generated based on the outputs of the convolutional neural network. The heatmap may indicate the quantities to which the different portions of the image contribute to the output of the convolutional neural network operating on the image. Related systems and articles of manufacture, including computer program products, are also provided.

Abstract: A phacoemulsification system having an imaging device configured to capture images of an eye and a phacoemulsification probe, a display, and a processor configured to receive an eye scan result providing a two-dimensional array of cataract thicknesses of the eye, find cutlines through which to cut the cataract into sections responsively to the two-dimensional array of cataract thicknesses, and render the images of the eye and the phacoemulsification probe with representations of the found cutlines through which to cut the cataract into sections to the display.

Abstract: In an imaging method an image is generated by an imaging device that includes a vessel structure of an object to be imaged and/or a device arranged in the object. A local asymmetrical contrast amplification algorithm is applied to the image to generate a filtered image that is displayed by a display device.

Abstract: A method, an apparatus, and a device for image processing and a training method thereof are provided. The training method includes obtaining a sample image set, the sample image set comprising a first number of sample images; constructing an image feature set based on the sample image set, the image feature set comprising an image feature extracted from each of the sample images in the sample image set; obtaining a training image set, the training image set comprising a second number of training images; constructing multiple training image pairs based on the training image set and the image feature set; and training the image processing model based on the multiple training image pairs.

Abstract: A method includes receiving a three-dimensional image dataset of a surgical site of a patient. The method also includes segmenting one or more anatomical features of the surgical site based on the three-dimensional image dataset. The method also includes receiving a two-dimensional image of the surgical site of the patient and registering the two-dimensional image to an image from the three-dimensional image dataset. The method also includes displaying a two-dimensional representation of the segmented one or more anatomical features based on the registered two-dimensional image and the image from the three-dimensional image dataset.

Abstract: A method may process an electronic image corresponding to a medical sample associated with a patient. The method may include receiving a selection of one or more artificial intelligence (AI) algorithms, receiving one or more whole slide images of a medical sample associated with a patient, performing a task on the whole slide images, using the one or more selected AI algorithms, the whole slide images being stored in a first container, the whole slide images being originated from a first user, the task comprising determining a characteristic of the medical sample in the whole slide images, based on the characteristic of the whole slide image, generating metadata associated with the whole slide image, and storing the metadata in a second container.

Abstract: An apparatus for enhancing an input phase distribution (I(xi)) is configured to retrieve the input phase distribution (I(xi)) and compute a baseline estimate (ƒ(xi)) as an estimate of a baseline (I2 (xi)) in the input phase distribution (I(xi)). The apparatus is further configured to obtain an output phase distribution (O(xi)) based on the baseline estimate (ƒ(xi)) and the input phase distribution (I(xi)).

Abstract: Systems, devices, computer-implemented methods, and/or computer program products that can facilitate pedestrian detection via a boundary cylinder model are addressed. In one example, a system can comprise a processor that executes computer executable components stored in memory. The computer-executable components can comprise a bounding cylinder model component that determines numerical values for height and radius parameters of a three-dimensional bounding cylinder model representing a pedestrian, and that generates the three-dimensional bounding cylinder model representing the pedestrian based on the numerical values.

Abstract: A computer-implemented method for training a machine learning system including: initializing parameters of the machine learning system and a metaparameter. Repeatedly carrying out the following as a loop: providing a batch of training data points and manipulating the provided training data points or a training method for optimizing the parameters of the machine learning system or a structure of the machine learning system based on the metaparameter. Ascertaining a cost function as a function of instantaneous parameters of the machine learning system and of the instantaneous metaparameters. Adapting the instantaneous parameters as a function of an ascertained first gradient, which has been ascertained with respect to the instantaneous parameters via the ascertained cost function for the training data points, and adapting the metaparameter as a function of a second gradient, which has been ascertained with respect to the metaparameter used in the preceding step via the ascertained cost function.

Abstract: Fiducial coordinates are obtained by aligning template with region of interest extracted from a workpiece image. Image values in the region of interest are projected along a template axis and the project values evaluated to establish a fiducial location which can be used as a reference location for locating workpiece areas for ion beam milling or other processing.

Abstract: A method and system of recognizing object edges and a computer-readable storage medium are provided. The method includes: obtaining an input image; recognizing the input image and obtaining a relative position of each object vertex and a corresponding image vertex thereof; determining a reference position of each object vertex in the input image according to the relative position of each object vertex and the corresponding image vertex thereof; performing corner point detection in a predetermined area where the reference position of the object vertex is located for each object vertex; determining an actual position of each object vertex in the input image according to a result of the corner point detection; and sequentially connecting adjacent object vertices to form edge lines to obtain the edges of the object with edges in the input image according to the actual position of each object vertex in the input image.

Abstract: A non-transitory computer-readable recording medium stores an information processing program for causing a computer to execute processing including: acquiring data that indicates a relationship between element actions for a plurality of element actions in an object period; acquiring an effective time that corresponds to an object action; and searching for a combination of two or more element actions that form the object action among the plurality of element actions for each divided section set by dividing the object period according to the acquired effective time on the basis of the acquired data.

Abstract: A method for determining a semantic free space in an environment of a vehicle comprises capturing a two dimensional visual image from the environment of the vehicle via a camera and determining a limitation of a free space within the visual image. Via a sensor, distance data of objects are captured and assigned to the visual image, and the limitation of the free space is transferred to a bird's-eye view based on the assigned distance data. For objects identified in the visual image a respective bounding box and a respective classification are determined. Objects limiting the free space are selected, and their bounding box is assigned to the limitation of the free space in the bird's-eye view. Finally, segments of the limitation of the free space are classified according to the classification of each bounding box of the selected objects.

Abstract: According to one embodiment, a learning method includes acquiring first multi-view images obtained by capturing a first subject and causing a statistical model to learn, based on first and second bokeh values output from the statistical model by inputting first and second images of the first multi-view images. The causing includes acquiring a first distance from the capture device to a first subject in the first image and a second distance from the capture device to a first subject in the second image, discriminating a relationship in length between the first and second distances, and causing the statistical model to learn such that a relationship in magnitude between the first and second bokeh values is equal to the discriminated relationship.

Abstract: Provided are an image processing circuit, a system-on-chip including the same, and a method of improving quality of a first image. The image processing circuit includes a tuning circuit configured to receive a segmentation map including pixel-by-pixel class inference information of the first image and a confidence map including confidence of the class inference information, determine classes of respective pixels of the first image, correction effects for each pixel of the image, and correction values indicating intensity of the correction effects based on the segmentation map and the confidence map, and generate a correction map based on the classes and the correction values of the respective pixels; and at least one correcting circuit configured to generate an enhanced image by applying correction effects according to the correction values to the respective pixels of the first image based on the correction map.

Abstract: The present disclosure provides a virtual viewpoint synthesis method, including: pre-processing a depth image with zero parallax corresponding to an original image to obtain a processed depth image; generating virtual viewpoint images corresponding to a plurality of virtual viewpoints respectively according to the processed depth image and the original image; and filling holes in the virtual viewpoint image to generate a plurality of filled virtual viewpoint images. The present disclosure further provides an electronic apparatus and a computer-readable medium.

Abstract: A scanning microscope system configured for material analysis and mineralogy comprising a first detector and a second detector, and a data-processing system comprising a data-storage component and a segmentation component. The data-storage component is configured for providing image(s) of a sample based on first emissions from a plurality of first scan locations. The segmentation component is configured for determining at least one or a plurality of second scan locations for at least one or a plurality of region(s) of the at least one image. The second detector is configured for detecting second emissions from at least one of the second scan locations of at least one of the regions. The system is further configured for determining the second scan location(s) for the region(s) and detecting the second emissions from the at least one of the second scan locations of the at least one of the regions in parallel.

Abstract: A system, apparatus, method and a computer readable storage medium for extracting an asset. The method captures a scene having a two-dimensional (2D) boundary in a field of view. The scene is analyzed to detect visual content on the 2D boundary. The visual content is extracted without capturing a visual field beyond the 2D boundary. The visual content is sent over a network interface for remote sharing.