Titlebook: Advances in Multimedia Information Processing – PCM 2017; 18th Pacific-Rim Con Bing Zeng,Qingming Huang,Xiaopeng Fan Conference proceedings

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An Introduction to Cooperativesption of the target. The method, called semantic R-CNN, extends RPN (Region Proposal Network) [.] by adding LSTM [.] module for processing natural language query text. LSTM [.] module take encoded query text and image descriptors as input and output the probability of the query text conditioned on v

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alabaster

Luiz Inácio Gaiger,Eliene Dos Anjospposes that common object patterns are sparse concerning transformations across images. The key issue is then how to take advantage of the interrelations among images. Since an image normally matches better with similar images containing the same object than noise images, we exploit the image matchi

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Introduction to Steady-State Systems with conditional random fields (CRFs), however, cause significant increase in model complexity and scattered distribution of pixels in border regions. To address these issues, we propose a novel approach combining random walk with FCNs to capture global features and refine border regions of segment

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一个姐姐

Introduction to Steady-State Systemson features, which could degrade retrieval performance. In this paper, we fuse appearance features and correlation features to exploit rich information of face videos for face video retrieval via a deep convolutional neural network. The network extracts appearance feature and correlation feature fro

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Cooperativity Theory in Biochemistryer, the cases of ambiguous viewpoint predicted by the convolutional neural network, especially for two peaks of high confidence viewpoint proposals, may specify a set of erroneous keypoints. To address the above issue, we present multiscale convolutional neural networks and propose a filter to ensur

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https://doi.org/10.1007/978-3-319-77383-4artificial intelligence; classification; computer vision; cryptography; data security; estimation; face re