Abstract: Techniques related to generating a fine super resolution image from a low resolution image including a person wearing a predetermined uniform are discussed. Such techniques include applying a pretrained convolutional neural network to a stacked image including image channels from a coarse super resolution image, label data corresponding to the coarse super resolution image from available labels relevant to the uniform, and pose data corresponding to the person to determine the fine super resolution image.

Abstract: Techniques related to generating a fine super resolution image from a low resolution image including a person wearing a predetermined uniform are discussed. Such techniques include applying a pretrained convolutional neural network to a stacked image including image channels from a coarse super resolution image, label data corresponding to the coarse super resolution image from available labels relevant to the uniform, and pose data corresponding to the person to determine the fine super resolution image.

Abstract: Techniques related to generating a fine super resolution image from a low resolution image including a person wearing a predetermined uniform are discussed. Such techniques include applying a pretrained convolutional neural network to a stacked image including image channels from a coarse super resolution image, label data corresponding to the coarse super resolution image from available labels relevant to the uniform, and pose data corresponding to the person to determine the fine super resolution image.

Abstract: Embodiments described herein provide an apparatus comprising a processor to separate a three-dimensional (3D) scene in a point cloud data set comprising a plurality of voxels into a 3D grid of cells, each cell in the 3D grid of cells comprising a plurality of faces, execute a 3D clustering algorithm to create a plurality of 3D clusters, define a transparency level for each face of each cell in the plurality of cells, detect a surface layer of cells for the plurality of clusters in the 3D scene, and delete, from the plurality of clusters, cells which are not in the surface layer of cells. Other embodiments may be described and claimed.

Abstract: Embodiments described herein provide an apparatus comprising a processor to separate a three-dimensional (3D) scene in a point cloud data set comprising a plurality of voxels into a 3D grid of cells, each cell in the 3D grid of cells comprising a plurality of faces, execute a 3D clustering algorithm to create a plurality of 3D clusters, define a transparency level for each face of each cell in the plurality of cells, detect a surface layer of cells for the plurality of clusters in the 3D scene, and delete, from the plurality of clusters, cells which are not in the surface layer of cells. Other embodiments may be described and claimed.

Abstract: Techniques related to generating a fine super resolution image from a low resolution image including a person wearing a predetermined uniform are discussed. Such techniques include applying a pretrained convolutional neural network to a stacked image including image channels from a coarse super resolution image, label data corresponding to the coarse super resolution image from available labels relevant to the uniform, and pose data corresponding to the person to determine the fine super resolution image.

Abstract: A system and computer implemented method is provided for monitoring dynamic application data. A request to monitor a sub-region within a display page of a user interface of a second application may be accepted in a first application. The first application may iteratively capture data during the operation of the second application. The first application may determine that an instance of the captured data matches data representing the requested sub-region or page and in response, may extract content associated with the requested sub-region from the captured data. The first or second application may display the extracted content, for example, for monitoring the requested sub-region of the second application.