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The neurotrophin brain-derived neurotrophic factor (BDNF) and its receptor TrkB participate in diverse neuronal functions, including activity-dependent synaptic plasticity that is crucial for learning and memory. On binding to BDNF, TrkB is not only autophosphorylated at tyrosine residues but also undergoes serine phosphorylation at S478 by the(More)
A fast inverted index based algorithm is introduced for multi-class action recognition. At first, we compute the shape-motion features of the automatically localized actor. Secondly, a binary state tree is built by hierarchically clustering of the extracted features, and the action states are the cluster centers. Then videos are represented as sequences of(More)
a r t i c l e i n f o Researchers have systematically investigated the influence of online reviews on consumer perceptions and decisions to purchase products, but hitherto have not attended to the presentation format. Increasingly, video reviews are making their way into various websites, and their impact on consumer perceptions is not yet known. While(More)
Goal Extracting meaningful contextual data from raw sensor datasets collected in the context of smart home Challenges  Heterogeneous sensor nodes  Analysis of noisy and huge collected datasets  Obtaining the ground truth Approach  Activity recognition with the means of machine learning algorithms  Time series analysis of daily power consumption (More)
Background learning is a pre-processing of motion detection which is a basis step of video analysis. For the static background, many previous works have already achieved good performance. However, the results on learning dynamic background are still much to be improved. To address this challenge, in this paper, a novel and practical method is proposed based(More)
Motion detection is a basis step for video processing. Previous works of motion detection based on deep learning need clean foreground or background images which always do not exist in practice. To address this challenge, a novel and practical method is proposed based on auto-encoder neural networks. First, the approximate background images are obtained via(More)