Abstract: An image encoder includes a processor and a memory. The memory includes instructions configured to cause the processor to perform operations. In one example implementation, the operations may include determining whether a dictionary item is available for replacing a block of an image being encoded, the determining based on a hierarchical lookup mechanism, and encoding the image along with reference information of the dictionary item in response to determining that the dictionary item is available. In one more example implementation, the operations may include performing principal component analysis (PCA) on a block to generate a corresponding projected block, the block being associated with a group of images, comparing the projected block with a corresponding threshold, descending the block recursively based on the threshold until a condition is satisfied, and identifying a left over block as a cluster upon satisfying of the condition.

Abstract: Provided is an information processing device that enables a virtual object to be displayed at an appropriate position in the real world. The information processing device includes a position estimation unit that estimates a current position in a first coordinate system, a display position setting unit that sets a display position of a virtual object in a third coordinate system on the basis of an environment database, virtual object information including the display position of the virtual object in a second coordinate system, and an observed image captured near the current position, a meta information generation unit that generates observation meta information, and an environment database management unit that compares observation data with environment data of the environment database to determine whether to add the observation data to the environment database.

Abstract: A differentiation system for differentiating cells includes an input device configured to receive holographic image data of a microscopic particle in suspension, holographic image data processing logic for converting the holographic image data to the frequency domain by performing a Fourier transform of the holographic image data, and a recognizer configured to determine characterization features of the holographic image data of the microscopic particle in the frequency domain for characterization of the microscopic particle, the characterization features comprising rotationally invariant features.

Abstract: A system and method for providing object recognition using artificial neural networks. The method includes capturing a plurality of reference images with a camera associated with an edge node on a communication network. The reference images are received by a centralized server on the communication network. The reference images are analyzed with a parent neural network of the centralized server to determine a subset of objects identified by the parent neural network in the reference images. One or more filters that are responsive to the subset of objects are selected from the parent neural network. A pruned neural network is created from only the one or more filters. The pruned neural network is deployed to the edge node. Real-time images are captured with the camera of the edge node and objects in the real-time images are identified with the pruned neural network.

Abstract: A method and apparatus for improving sensitivity of wafer detection, and a storage medium are provided. The method including: acquiring a gray-scale image of a peripheral circuit region of a wafer; dividing the gray-scale image into at least one pixel region; determining a repeated image region in each pixel region, in which the repeated image region is a region with N*M pixels where M pixels on a same column in the repeated image region have a same gray-scale value, and N and M are integers greater than 0; and determining position information where interference superposition occurs in the peripheral circuit region of the wafer according to all repeated image regions in the gray-scale image.

Abstract: An object is to improve character recognition accuracy of handwritten characters, originally a single continuous character string, described discontinuously. An image area corresponding to a handwritten character is separated from a document image obtained by scanning a document and a character block including characters having the same baseline is extracted. Then, in a case where a plurality of character blocks is extracted from the first image area, a single character block is generated by combining character blocks based on a position relationship of the plurality of character blocks.

Abstract: Systems and methods for determining a current state, of at least one traffic light, for use in controlling an autonomous vehicle are described herein. Implementations determine, based on a pose instance of the autonomous vehicle and a stored mapping of an environment of the autonomous vehicle, a region of the environment includes the traffic light and a configuration that is assigned to the traffic light. Further, those implementations process an image capturing the region, using a machine learning classifier, to generate predicted output associated with multiple candidate states of the traffic light, and determine a current state of the traffic light based on the predicted output. Processing the image using the machine learning classifier can be based on the configuration of the traffic light.

Abstract: A text recognition method and apparatus disclosed. The text recognition method includes: obtaining a to-be-detected image; determining a target text detection area in the to-be-detected image, where the target text detection area includes target text in the to-be-detected image, and the target text detection area is a polygonal area including m vertex pairs, m being a positive integer greater than 2; correcting the polygonal area to m?1 rectangular areas to obtain a corrected target text detection area; and performing text recognition on the corrected target text detection area to determine the target text, and outputting the target text.

Abstract: The present invention relates to the field of instruments for visualizing the inner structures of the human body, and in particular of the eye. More specifically, its object is an optical coherence tomography system and method of the “Fourier-domain” type with the removal of unwanted artifacts through digital image processing.

Abstract: Techniques for updating data operations in a perception system are discussed herein. A vehicle may use a perception system to capture data about an environment proximate to the vehicle. The perception system may receive image data, lidar data, and/or radar data to determine information about an object in the environment. As different sensors may be associated with different time periods for capturing and/or processing operations, the techniques include updating object data with data from sensors associated with a shorter time period to generate intermediate object data.

Abstract: The present disclosure describes a method, an apparatus, and a non-transitory computer-readable medium for detecting sensitive text information such as privacy-related text information from a signal and modifying the signal by removing the detected sensitive text information therefrom. The apparatus receives the signal such as an image, a video clip, or an audio clip, and recognizes a text string therefrom. The apparatus then detects, from the text string, a substring based on a similarity between the substring and a regular expression, and modifies the signal by removing information related to the detected substring from the signal.

Abstract: The present disclosure provides a method for correcting an OCR text position, a storage medium and an electronic device. The method includes: determining a first slope of each text block in an OCR recognition result of a to-be-processed image; fitting a tilt field function in accordance with the first slope of each text block; determining an offset value of each text block in accordance with the tilt field function; and correcting a position of each text block in accordance with the offset value.

Abstract: The present disclosure relates to a handwritten text recognition method, including: acquiring an information sequence including a plurality of track points of handwritten text, wherein information on each track point comprises its abscissa, writing time and writing state value; dividing the plurality of track points into a plurality of strokes according to the writing state value of each track point, the writing state value including a first value representative of stroke pen-up and a second value representative of stroke pen-down, respectively; calculating a first segmentation threshold of the handwritten text; determining a first text segmentation point according to a result of comparison between an absolute value of a difference between abscissas of a start track point of one stroke and an end track point of its previous stroke and the first segmentation threshold; and performing text segmentation according to the first text segmentation point to obtain a text segmentation result.

Abstract: According to an embodiment, a reading system includes a first extractor and a reader. The first extractor extracts, from an image in which a meter is imaged, a first region surrounded with a first contour, and a second region surrounded with a second contour positioned outward of the first contour. The reader calculates a first indication based on the first region, calculates a second indication based on the second region, calculates a first score relating to the first indication based on the first region, and calculates a second score relating to the second indication based on the second region.

Abstract: An information processing apparatus comprises a generating unit configured to generate supervised data relating to a topological invariant based on a topological property relating to supervised data corresponding to input data, and a training unit configured to perform, based on a geometric property relating to an output from a classifier to which the input data is input and the supervised data generated by the generating unit, training of the classifier.

Abstract: A server includes a communications interface; and a processor connected with the communications interface, the processor configured to: receive, from each of a plurality of capture nodes: (i) an initial point cloud depicting a portion of a capture volume, and (ii) boundary values corresponding to the initial point cloud; generate a bounding box from the boundary values received from the capture nodes; select respective portions of each initial point cloud based on the bounding box; and combine the selected portions to generate a combined point cloud.

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 method of extracting high-frequency temporal information from images or video recorded with a rolling shutter-based imager includes the steps of acquiring image data using the rolling shutter-based imager; and extracting time-domain frequency information from the image data based on two or more lines of pixels in the image data.

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: 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.