Abstract: An improved neural network is disclosed that supports rapid retraining using human feedback. A weighted ensemble of Extreme Learning Machines (ELMs) is used to implement a model. The ensemble of ELMs may be trained in parallel with a variation in individual parameters gridding a parameter set selected to achieve consistent accurate model results when the model is trained and subsequently retrained when user feedback data become available. An exemplary application is the scoring of resumes.

Abstract: Embodiments of the present disclosure relate to image processing. In at least one embodiment, a method comprises: receiving the video file; segmenting the video file, determining foreground in the video file, estimating motion in the video file, determining objects in the video file, partitioning the video file and encoding the video file.

Abstract: A technique for foreground determination includes analyzing pixels that are deemed to be changing between frames, and applying a filtration technique that is based on fractal methods. Implementations include applying a filter that is designed to eliminate structures of dimensionality less than unity while preserving those of dimensionality unity and greater. The technique may be performed in real-time and makes use of a variable threshold for foreground determination and image segmentation techniques.

Abstract: A method and device for encoding video including determining objects within a frame at least partially based on movement characteristics of underlying pixels and partitioning the frame into blocks by considering a plurality of partitioning options, such partitioning favoring options that result in different objects being placed in different blocks.

Abstract: Embodiments of the present disclosure relate to image processing. In at least one embodiment, a method comprises: receiving the video file; segmenting the video file, determining foreground in the video file, estimating motion in the video file, determining objects in the video file, partitioning the video file and encoding the video file.

Abstract: A video encoding system is disclosed to process a video file into one or more desired formats. The video file may have portions processed in parallel. The video encoding system may include a scalable computing resource. The scalable computing resource may be provided by a cloud computing platform.

Abstract: A method and device for encoding video including determining objects within a frame at least partially based on movement characteristics of underlying pixels and partitioning the frame into blocks by considering a plurality of partitioning options, such partitioning favoring options that result in different objects being placed in different blocks.

Abstract: A method and apparatus for unsupervised segmentation of an image is provided. In some exemplary embodiments, the method adjusts a segmentation parameter of a traditional graph-based segmentation algorithm along the image to generate a segmentation map that is perceptually reasonable for a human observer. In some embodiments, the method reduces over-segmentation and under-segmentation of the image.

Abstract: Systems and method for object characterization include generating a classifier that defines a decision hyperplane separating a first classification region of a virtual feature space from a second classification region of the virtual feature space. Input information is provided to the classifier, and a number of classifications are received from the classifier. A distribution of the classifications is determined and used to generate a prediction.

Abstract: A method and apparatus for unsupervised segmentation of an image is provided. In some exemplary embodiments, the method adjusts a segmentation parameter of a traditional graph-based segmentation algorithm along the image to generate a segmentation map that is perceptually reasonable for a human observer. In some embodiments, the method reduces over-segmentation and under-segmentation of the image.

Abstract: A technique for foreground determination includes analyzing pixels that are deemed to be changing between frames, and applying a filtration technique that is based on fractal methods. Implementations include applying a filter that is designed to eliminate structures of dimensionality less than unity while preserving those of dimensionality unity and greater. The technique may be performed in real-time and makes use of a variable threshold for foreground determination and image segmentation techniques.

Abstract: A method and device for encoding video including determining objects within a frame at least partially based on movement characteristics of underlying pixels and partitioning the frame into blocks by considering a plurality of partitioning options, such partitioning favoring options that result in different objects being placed in different blocks.

Abstract: A method and apparatus for unsupervised segmentation of an image is provided. In some exemplary embodiments, the method adjusts a segmentation parameter of a traditional graph-based segmentation algorithm along the image to generate a segmentation map that is perceptually reasonable for a human observer. In some embodiments, the method reduces over-segmentation and under-segmentation of the image.

Abstract: In embodiments, a system for encoding video is configured to receive video data comprising a frame and identify a partitioning option. The system identifies at least one characteristic corresponding to the partitioning option, provides the at least one characteristic, as input, to a classifier, and determines, based on the classifier, whether to partition the frame according to the identified partitioning option.

Abstract: One embodiment relates to a method of model-based optical metrology. An area of a geometrical structure of dispersive materials on a substrate is illuminated with polarized incident electromagnetic radiation using an illuminator of a scatterometer apparatus. Spectral components of the incident electromagnetic radiation reflected from the area are measured using a detector of the scatterometer apparatus. Using a computer for the scatterometer apparatus, parameter values are determined that minimize an objective function which represents a difference between the measured spectral components and computed spectral components based on a parameterized model of the geometrical structure. Steps for determining the parameter values that minimize the objective function include: computing a solution to state equations driven by a function representing the incident electromagnetic radiation, and computing a solution to an adjoint to the state equations. Other embodiments and features are also disclosed.

Abstract: A method and device for encoding video including determining objects within a frame at least partially based on movement characteristics of underlying pixels and partitioning the frame into blocks by considering a plurality of partitioning options, such partitioning favoring options that result in different objects being placed in different blocks.

Abstract: A video encoding system is disclosed to process a video file into one or more desired formats. The video file may have portions processed in parallel. The video encoding system may include a scalable computing resource. The scalable computing resource may be provided by a cloud computing platform.

Abstract: In one embodiment, an image is broken up into multiple regions or segments, where each segment may be of arbitrary shape, and a transform (multi-scale or otherwise) is applied on the set of segments. In another embodiment, pattern adaptive prediction is used when predicting the next finer level of the transform pyramid. The pattern adaptive prediction uses the parent grid to determine what geometry of a filter is to be used when predicting the child grid. At the boundaries of the domain, the pattern adaptive prediction can coupled with the domain adaptive prediction technique.

Abstract: In one embodiment, an image is broken up into multiple regions or segments, where each segment may be of arbitrary shape, and a transform (multi-scale or otherwise) is applied on the set of segments. In another embodiment, pattern adaptive prediction is used when predicting the next finer level of the transform pyramid. The pattern adaptive prediction uses the parent grid to determine what geometry of a filter is to be used when predicting the child grid. At the boundaries of the domain, the pattern adaptive prediction can coupled with the domain adaptive prediction technique.

Abstract: In one embodiment, an image is broken up into multiple regions or segments, where each segment may be of arbitrary shape, and a transform (multi-scale or otherwise) is applied on the set of segments. In another embodiment, pattern adaptive prediction is used when predicting the next finer level of the transform pyramid. The pattern adaptive prediction uses the parent grid to determine what geometry of a filter is to be used when predicting the child grid. At the boundaries of the domain, the pattern adaptive prediction can be coupled with the domain adaptive prediction technique.