Abstract: Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

Abstract: A laser radar system according to the present invention includes: a light source to output light having a first frequency in a first period and light having a second frequency in a second period; an optical splitter to split the lights, outputted from the light source, into signal light and local oscillator light; an optical modulator to modulate the signal light into pulsed light; an optical antenna to output the pulsed light into space and to receive, as reception light, the scattered light from a target; an optical heterodyne receiver to perform heterodyne detection on the reception light by using the local oscillator light; and a measurement unit to measure the distance to the target or the movement characteristics of the target by using the reception signal detected by the optical heterodyne receiver, wherein the optical heterodyne receiver performs the heterodyne detection on the first frequency of the reception light by using the second frequency of the local oscillator light.

Abstract: Disclosed embodiments are a computing system and a computer-implemented method related to predicting travel time by using adjacent travel time. The prediction may be based on correcting the nominal predictive travel time estimation using a relation between the predictive travel time estimation and the nominal predictive travel time estimation of a nearby commuting instance in a similar direction. This allows a reduced number of queries to the geographic information system, which may save time, costs and conserve communication resources.

Abstract: A method for video processing is provided. The method includes determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, parameters of a cross-component linear model (CCLM) based on two or four chroma samples and/or corresponding luma samples; and performing the conversion based on the determining.

Abstract: Methods and systems for detecting abnormal application behavior include determining a vector representation of a first syscall graph that is generated by a first application, the vector representation including a representation of a distribution of subgraphs of the first syscall graph. The vector representation of the first syscall graph is compared to one or more second syscall graphs that are generated by respective second applications to determine respective similarity scores. It is determined that the first application is behaving abnormally based on the similarity scores, and a security action is performed responsive to the determination that the first application is behaving abnormally.

Abstract: Disclosed is an image data encoding/decoding method and apparatus. A method for decoding a 360-degree image comprises the steps of: receiving a bitstream obtained by encoding a 360-degree image; generating a prediction image by making reference to syntax information obtained from the received bitstream; combining the generated prediction image with a residual image obtained by dequantizing and inverse-transforming the bitstream, so as to obtain a decoded image; and reconstructing the decoded image into a 360-degree image according to a projection format.

Abstract: Disclosed is an image data encoding/decoding method and apparatus. A method for decoding a 360-degree image comprises the steps of: receiving a bitstream obtained by encoding a 360-degree image; generating a prediction image by making reference to syntax information obtained from the received bitstream; combining the generated prediction image with a residual image obtained by dequantizing and inverse-transforming the bitstream, so as to obtain a decoded image; and reconstructing the decoded image into a 360-degree image according to a projection format.

Abstract: Disclosed is an image data encoding/decoding method and apparatus. A method for decoding a 360-degree image comprises the steps of: receiving a bitstream obtained by encoding a 360-degree image; generating a prediction image by making reference to syntax information obtained from the received bitstream; combining the generated prediction image with a residual image obtained by dequantizing and inverse-transforming the bitstream, so as to obtain a decoded image; and reconstructing the decoded image into a 360-degree image according to a projection format.

Abstract: Examples of a light field metrology system for use with a display are disclosed. The light field metrology may capture images of a projected light field, and determine focus depths (or lateral focus positions) for various regions of the light field using the captured images. The determined focus depths (or lateral positions) may then be compared with intended focus depths (or lateral positions), to quantify the imperfections of the display. Based on the measured imperfections, an appropriate error correction may be performed on the light field to correct for the measured imperfections. The display can be an optical display element in a head mounted display, for example, an optical display element capable of generating multiple depth planes or a light field display.

Abstract: A method for decoding a 360-degree image includes: receiving a bitstream obtained by encoding a 360-degree image; generating a prediction image by making reference to syntax information obtained from the received bitstream; combining the generated prediction image with a residual image obtained by dequantizing and inverse-transforming the bitstream to obtain a decoded image; and reconstructing the decoded image into a 360-degree image according to a projection format.

Abstract: A device may determine an association between a second set of parameters and a third set of parameters using a pseudoinversion network and a multiple regression procedure. The device may determine semantic embeddings based on a set of semantic descriptions of the second set of parameters. The device may determine a semantic similarity between parameters of the second set of parameters based on the semantic embeddings. The device may determine a consistency error based on the semantic similarity. The device may generate, using a regression-based learning model technique, a matrix representing an association between the second set of parameters and the third set of parameters based on the association and the consistency error. The device may perform an action based on the matrix.

Abstract: This disclosure is directed to coding a multi-view signal, which includes processing a list of plurality of motion vector candidates associated with a coding block of a current picture in a dependent view of the multi-view signal. Such processing includes estimating a first motion vector based on a second motion vector associated with a reference block in a current picture of a reference view of the multi-view signal, the reference block corresponding to the coding block of the current picture in the dependent view. The first motion vector is added into the list, and an index is used that specifies at least one candidate from the list to be used for motion-compensated prediction. The coding block in the current picture is coded by performing the motion-compensated prediction based on the at least one candidate indicated by the index.

Abstract: An information processing apparatus includes an acquisition unit, a calculation unit, and a generation unit. The acquisition unit acquires information including information regarding multiple nodes and information regarding multiple links connecting the multiple nodes and acquires constraint information regarding node pairs included in the multiple nodes. The constraint information includes a positive constraint and a negative constraint. The calculation unit calculates, for each of multiple clusters, a classification proportion into which the multiple nodes are classified and calculates a degree of importance of each of the multiple clusters. The classification proportion represents a proportion in which each of the multiple nodes is classified as one of the multiple clusters. The generation unit generates a probability model for performing probabilistic clustering on the multiple nodes.

Abstract: A streaming system includes a streaming server and a client device. The streaming server is configured to train an interactive frame prediction model based on streaming data, a user input and metadata associated with the user input, encode the streaming data by selectively using a predicted frame generated based on the trained interactive frame prediction model and transmit the trained interactive frame prediction model and the encoded streaming data. The client device is configured to receive the trained interactive frame prediction model and the encoded streaming data, and decode the encoded streaming data based on the trained interactive frame prediction model to provide recovered streaming data to a user.

Abstract: Embodiments of the invention utilize a feature-extraction approach and/or a matching approach in combination with a nonparametric approach to estimate the proportion of documents in each of multiple labeled categories with high accuracy. The feature-extraction approach automatically generates continuously valued text features optimized for estimating the category proportions, and the matching approach constructs a matched set that closely resembles a data set that is unobserved based on an observed set, thereby improving the degree to which the distributions of the observed and unobserved sets resemble each other.

Abstract: A system and method for stitching separately encoded MPEG video fragments, each representing a different rectangular area of the screen together into one single full-screen MPEG encoded video fragment.

Abstract: A method for video decoding includes decoding prediction information of a current block from a coded video bitstream, the prediction information being indicative of a prediction mode that is based on a candidate list. The method includes constructing, in response to the prediction mode, the candidate list that includes a plurality of side candidates that includes (i) a first side candidate having a first corner that is at a middle point of a side of the block and a second corner that is one of above and below the middle point of the side of the block, and (ii) a second side candidate located between the first side candidate and a corner block neighboring the current block. The method further includes reconstructing at least one sample of the current block according to motion information from the plurality of side candidates.

Abstract: In an embodiment, a method includes receiving a trigger of machine learning model generation. In addition, the method includes algorithmically eliminating at least some of rows and at least some of columns of a training dataset, the algorithmically eliminating yielding a size-reduced training dataset. The method additionally includes generating, for a prediction target, a plurality of machine learning models via a plurality of machine learning algorithms. The method also includes measuring prediction accuracies of the plurality of machine learning models relative to the prediction target. Furthermore, the method includes selecting a particular machine learning model. Moreover, the method includes applying the particular machine learning model to a data source.

Abstract: The present disclosure relates to systems and methods for facing a tissue block. In some embodiments, a method is provided for facing a tissue block that includes imaging a tissue block to generate imaging data of the tissue block, the tissue block comprising a tissue sample embedded in an embedding material, estimating, based on the imaging data, a depth profile of the tissue block, wherein the depth profile comprises a thickness of the embedding material to be removed to expose the tissue sample to a pre-determined criteria, and removing the thickness of the embedding material to expose the tissue to the pre-determined criteria.

Abstract: Provided is a method and system for detection of anomalous work pieces that includes computing at least one deviation data signal for a target data signal of a target work piece with respect to reference data signals recorded for a corresponding production process step of a set of reference work pieces, performing a stepwise anomaly detection by data processing of the at least one computed deviation data signal and a process type indicator indicating a type of the production process step using a trained anomaly detection data model to calculate for each time step or path length step of the production process step an anomaly probability that the respective time step or path length step is anomalous, and classifying the target work piece and/or the production process step as being anomalous or not anomalous on the basis of the calculated anomaly probabilities.