Temporal dimension

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  • Event recognition methods can be roughly categorized into model-based methods and appearance-based techniques. Model-based approaches relied on various models, includ- ing HMM [35], coupled HMM [3], and Dynamic Bayesian Network [33], to model the temporal evolution. The relationships among different body parts and regions are also modeled in [3], [35], in which object tracking needs to be conducted at first before model learning.

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  • The impetus to write a book on the riverine ecosystem synthesis emerged at the 2005 annual meeting of the North American Benthological Society in New Orleans, and barely 2 months later, we signed a contract with Academic Press. This book was to be an expansion of a manuscript that was In Press at that time in River Research and Applications (Thorp et al., 2006).

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  • Main Receive Aperture and Analog Beamforming Data to be Processed The Processing Needs and Major Issues Temporal DOF Reduction Adaptive Filtering with Needed and Sample-Supportable DOF and Embedded CFAR Processing 70.6 Scan-To-Scan Track-Before-Detect Processing 70.7 Real-Time Nonhomogeneity Detection and Sample Conditioning and Selection 70.8 Space or Space-Range Adaptive Pre-Suppression of Jammers 70.9 A STAP Example with a Revisit to Analog Beamforming 70.

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  • Religions have too often been used to justify the violation of human rights, in part through the hierarchical and selective use of role ethics and the postponement of temporal justice to divine judgment or future karmic consequences. Yet the world religions have also provided a constant voice of critique against the violation of human rights by calling for equality, and universal compassion and love, calls which reach far beyond the mere protection of human rights.

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  • Video sources produce data at very high bit rates. In many applications, the available bandwidth is usually very limited. For example, the bit rate produced by a 30 frame/s color common intermediate format (CIF) (352288) video source is 73 Mbits/s. In order to transmit such a sequence over a 64 Kbits/s channel (e.g., ISDNline), we need to compress the video sequence by a factor of 1140. A simple approach is to subsample the sequence in time and space. For example, if we subsample both chroma components by 2 in each dimension, i.e.

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  • Our goal is to develop automated methods for the segmentation of threedimensional biomedical images. Here, we describe the segmentation of confocal microscopy images of bee brains (20 individuals) by registration to one or several atlas images. Registration is performed by a highly parallel implementation of an entropy-based nonrigid registration algorithm using B-spline transformations. We present and evaluate different methods to solve the correspondence problem in atlas based registration.

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  • Mining retrospective events from text streams has been an important research topic. Classic text representation model (i.e., vector space model) cannot model temporal aspects of documents. To address it, we proposed a novel burst-based text representation model, denoted as BurstVSM. BurstVSM corresponds dimensions to bursty features instead of terms, which can capture semantic and temporal information.

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