Large scale video copy detection task requires compact feature insensitive to various copy changes. Based on local feature trajectory behavior we discover invariant visual patterns for generating robust feature. Bag o...
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This paper presents a partial matching strategy for phrase-based statistical machine translation (PBSMT). Source phrases which do not appear in the training corpus can be translated by word substitution according to p...
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Dynamic description logic (DDL) is among the few emerging service composition solutions through logical reasoning. To overcome low efficiency and lacking context-aware support of DDL reasoning, we propose a new DDL-ba...
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Firstly, a new Clustering algorithm based on Hyper Surface (CHS) is put forward in this paper. CHS needs no domain knowledge to determine input parameters. However, it is difficult to process locally dense data for CH...
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Video copy detection is essentially a problem of large scale pattern matching. Various copy attacks which change the visual appearance impose hazard on this task. Based on the spatio-temporal consistency, our algorith...
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This paper presents a partial matching strategy for phrase-based statistical machine translation (PBSMT). Source phrases which do not appear in the training corpus can be translated by word substitution according to p...
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This paper proposes a novel maximum entropy based rule selection (MERS) model for syntax-based statistical machine translation (SMT). The MERS model combines local contextual information around rules and information o...
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This paper proposes a novel lexicalized approach for rule selection for syntax-based statistical machine translation (SMT). We build maximum entropy (MaxEnt) models which combine rich context information for selecting...
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In this paper, we specially propose a hierarchical framework for movie content analysis. The purpose of our work is trying to realize computers' understanding for movie content, especially "Who, What, Where, ...
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Analytical study or designing of large‐scale nonlinear neural circuits, especially for chaotic neural circuits, is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framewo...
Analytical study or designing of large‐scale nonlinear neural circuits, especially for chaotic neural circuits, is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells’ dynamical equations. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system, and we proved that if a neural system works in a non‐chaotic way, a suitable fuzzy logical framework can be found and we can analyze or design such kind neural system similar to analyze or design a digit computer, but if a neural system works in a chaotic way, an approximation is needed for understanding the function of such neural system.
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