Abstract: The present disclosure provides methods and systems for task adaptation using fuzzy deep learning architecture. In the present disclosure, a low-shot approach for knee injury classification is proposed along with a deep learning architecture utilizing a fuzzy layer. For the low-shot approach, a stage of knowledge transfer takes place from a first classification task (source task) to a second classification task (target task) through a task adaptation approach. The first classification task and the second classification task are two related diagnoses of the knee, where sufficient labeled samples are available for first classification task but very few labeled samples are available for and the second classification task. Further, the trained fuzzy deep learning architecture is used to generate pseudo-labels for a collection of unlabeled samples available for and the second classification task.

Abstract: Optical images in remote sensing are contaminated by cloud cover and bad weather conditions and are only available during the daytime. Whereas SAR images are completely cloud free, independent of weather conditions and can be acquired both during the day and at night. However, due to the speckle effect and side looking imaging mechanism of SAR images, they are not easily interpretable by untrained people. To address this issue, the present disclosure provides a method and system for LULC guided SAR visualization, wherein a GAN is trained to translate SAR images to optical images for visualization. A given SAR image is fed into a first generator of the GAN to obtain LULC map which is then concatenated with the SAR image and fed into a second generator of the GAN to generate an optical image. The LULC map provides semantic information required for generation of more realistic optical image.

Abstract: State of the art image processing techniques such as background subtraction, and Convolutional Neural Network based approaches, when used for change detection, fail to support certain datasets. The disclosure herein generally relates to semantic change detection, and, more particularly, to a method and system for semantic change detection using a deep neural network feature correlation approach. An adaptive correlation layer is used by the system, which determines extent of computation required at pixel level, based on amount of information at pixels, and uses this information in further computation done for the semantic change detection. Information on the determined extent of computation required is then used to extract semantic features, which is then used to compute one or more correlation maps between the at least one feature map of a test image and corresponding reference image. Further the semantic changes are determined from the one or more correlation maps.

Abstract: State of the art image processing techniques such as background subtraction, and Convolutional Neural Network based approaches, when used for change detection, fail to support certain datasets. The disclosure herein generally relates to semantic change detection, and, more particularly, to a method and system for semantic change detection using a deep neural network feature correlation approach. An adaptive correlation layer is used by the system, which determines extent of computation required at pixel level, based on amount of information at pixels, and uses this information in further computation done for the semantic change detection. Information on the determined extent of computation required is then used to extract semantic features, which is then used to compute one or more correlation maps between the at least one feature map of a test image and corresponding reference image. Further the semantic changes are determined from the one or more correlation maps.

Abstract: A dynamic AC prediction technique is implemented in a data partition mode which automatically disables AC prediction for encoding the current macroblock in the next packet when packet overflow occurs. Otherwise, when there is no overflow, AC prediction remains enabled to maintain compression efficiency. More particularly, in the preferred embodiment, a determination is first made whether a macroblock causes a packet overflow if it is encoded in the current packet. If so, a new packet is initiated into which the macroblock is encoded without AC prediction as the first macroblock. Otherwise, the macroblock with AC prediction remains in the current packet and a new macroblock is encoded.

Abstract: A more efficient motion estimation process that utilizes a plurality of predicted start points (e.g., two predicted start points) based on blocks adjacent to the current block together with other improvements and requires minimal system resources (e.g., hardware resources and CPU processing) in its hardware implementation is provided. More particularly, the motion estimation technique in accordance with the present invention performs a plurality of coarse searches (either sequentially or in parallel) using a plurality of predicted start positions followed by a fine search.

Abstract: A VLC data transfer interface is presented that allows digital data to be packed and assembled according to a format selectable from a number of formats while the data is being transferred to a desired destination.

Abstract: A VLC data transfer interface is presented that allows digital data to be packed and assembled according to a format selectable from a number of formats while the data is being transferred to a desired destination.

Abstract: A VLC data transfer interface is presented that allows digital data to be packed and assembled according to a format selectable from a number of formats while the data is being transferred to a desired destination.

Abstract: A dynamic AC prediction technique is implemented in a data partition mode which automatically disables AC prediction for encoding the current macroblock in the next packet when packet overflow occurs. Otherwise, when there is no overflow, AC prediction remains enabled to maintain compression efficiency. More particularly, in the preferred embodiment, a determination is first made whether a macroblock causes a packet overflow if it is encoded in the current packet. If so, a new packet is initiated into which the macroblock is encoded without AC prediction as the first macroblock. Otherwise, the macroblock with AC prediction remains in the current packet and a new macroblock is encoded.

Abstract: A dynamic AC prediction technique is implemented in a data partition mode which automatically disables AC prediction for encoding the current macroblock in the next packet when packet overflow occurs. Otherwise, when there is no overflow, AC prediction remains enabled to maintain compression efficiency. More particularly, in the preferred embodiment, a determination is first made whether a macroblock causes a packet overflow if it is encoded in the current packet. If so, a new packet is initiated into which the macroblock is encoded without AC prediction as the first macroblock. Otherwise, the macroblock with AC prediction remains in the current packet and a new macroblock is encoded.

Abstract: A VLC data transfer interface is presented that allows digital data to be packed and assembled according to a format selectable from a number of formats while the data is being transferred to a desired destination.

Abstract: A dynamic AC prediction technique is implemented in a data partition mode which automatically disables AC prediction for encoding the current macroblock in the next packet when packet overflow occurs. Otherwise, when there is no overflow, AC prediction remains enabled to maintain compression efficiency. More particularly, in the preferred embodiment, a determination is first made whether a macroblock causes a packet overflow if it is encoded in the current packet. If so, a new packet is initiated into which the macroblock is encoded without AC prediction as the first macroblock. Otherwise, the macroblock with AC prediction remains in the current packet and a new macroblock is encoded.

Abstract: A more efficient motion estimation process that utilizes a plurality of predicted start points (e.g., two predicted start points) based on blocks adjacent to the current block together with other improvements and requires minimal system resources (e.g., hardware resources and CPU processing) in its hardware implementation is provided. More particularly, the motion estimation technique in accordance with the present invention performs a plurality of coarse searches (either sequentially or in parallel) using a plurality of predicted start positions followed by a fine search.

Abstract: An intelligent memory system, method, and computer program product for enabling stand-alone or distributed client-server software applications to operate at maximum speeds on a personal computer and the like. An intelligent memory allows the acceleration of computer software processes through process virtual memory, application optimization, multiprocessor control, and system strategies. The intelligent memory includes both control logic and memory. The control logic uses an application database and system database to determine a set of modifications to the computer, application, and/or operating system, while the memory stores the application and allows the control logic to implement the set of modifications.

Abstract: An intelligent memory system, method, and computer program product for enabling stand-alone or distributed client-server software applications to operate at maximum speeds on a personal computer and the like. An intelligent memory (IM) allows the acceleration of computer software processes through process virtual memory, application optimization, multiprocessor control, and system strategies. The IM includes both control logic and memory. The control logic uses an application database and system database to determine a set of modifications to the computer, application, and/or operating system, while the memory stores the application and allows the control logic to implement the set of modifications. A remote performance management system is also described which allows an IM service provider to supply the infrastructure to clients (e.g., e-businesses and the like who run World Wide Web servers) to facilitate and accelerate their content offerings to end user clients (i.e., consumers).