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Convolutional Neural Networks (CNNs) with Bilinear Pooling, initially in their full form and later using compact representations, have yielded impressive performance gains on a wide range of visual tasks, including fine-grained visual categorization, visual question answering, face recognition, and description of texture and style. The key to their success lies in the spatially invariant modeling...
Temporal segmentation of human motion into plausible motion primitives is central to understanding and building computational models of human motion. Several issues contribute to the challenge of discovering motion primitives: the exponential nature of all possible movement combinations, the variability in the temporal scale of human actions, and the complexity of representing articulated motion....
Automatic facial image analysis has been a long standing research problem in computer vision. A key component in facial image analysis, largely conditioning the success of subsequent algorithms (e.g. facial expression recognition), is to define a vocabulary of possible dynamic facial events. To date, that vocabulary has come from the anatomically-based Facial Action Coding System (FACS) or more subjective...
In this paper we present results from test and quantitative analysis of leading hypervisors Xen, Kvm and Vmware. Our test comparison was carried out using benchmarks which can performance on the overall performance, performance isolation, and scalability of virtual machines running on these three hypervisors. To compare, we need to measure the efficiency of the virtualization technologies. We define...
The paper presents a framework for distributed embedded applications that can be used to engineer open, and the same time, predictable embedded systems. Applications are composed from components (actors), which communicate transparently by exchanging labeled messages (signals) over a real-time network. The signals are exchanged at precisely specified time instants, in accordance with the Distributed...
Temporal segmentation of human motion into actions is a crucial step for understanding and building computational models of human motion. Several issues contribute to the challenge of this task. These include the large variability in the temporal scale and periodicity of human actions, as well as the exponential nature of all possible movement combinations. We formulate the temporal segmentation problem...
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