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We proposed a novel method of feature extraction for multi-modal images called modality-convolution. It extracts both the intra- and inter-modality information. Whats more, it completes the data fusion at pixel-level so that the complementarity of information contained in multi-modal data is fully utilized. Based on the modality-convolution, we describe a modality-CNN for multi-modal gesture recognition...
Image emotion analysis is a new and challenging research direction that gains more and more attention in the research community. Most previous works in this field only use common or generic features, and have hard restrictions on training images, such as scale, resolution, etc. Inspired by scale-space theories and psychology theories of color, we propose a procedure to extract interpretive features...
Big data techniques has been applied to power grid for the evaluation and prediction of grid conditions. However, the raw data quality rarely can meet the requirement of precise data analytics since raw data set usually contains samples with missing data to which the common data mining models are sensitive. Though classic interpolation or neural network methods can been used to fill the gaps of missing...
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