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Manifold-ranking based image retrieval
TLDR
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Expand
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A user attention model for video summarization
TLDR
In this paper, we present a generic framework of video summarization based on the modeling of viewer's attention. Expand
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Blur detection for digital images using wavelet transform
TLDR
A new blur detection scheme is proposed in this paper, which can determine whether an image is blurred or not and to what extent animage is blurred. Expand
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Image annotation via graph learning
TLDR
We propose a Nearest Spanning Chain (NSC) method to construct image-based graph, whose edge-weights are derived from the chain-wise statistical information instead of the traditional pairwise similarities. Expand
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An efficient and effective region-based image retrieval framework
TLDR
An image retrieval framework that integrates efficient region-based representation in terms of storage and complexity and effective on-line learning capability is proposed. Expand
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Online video recommendation based on multimodal fusion and relevance feedback
TLDR
This paper presents a novel online video recommendation system based on multimodal fusion and relevance feedback to automatically adjust intra-weights within each modality by users' click-though data. Expand
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A probabilistic model for retrospective news event detection
TLDR
We propose a probabilistic model to incorporate both content and time information in a unified framework. Expand
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Learning in Region-Based Image Retrieval
TLDR
In this paper, several effective learning algorithms using global image representations are adjusted and introduced to regionbased image retrieval (RBIR). Expand
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Toward a unified approach to statistical language modeling for Chinese
TLDR
This article presents a unified approach to Chinese statistical language modeling (SLM) that automatically gathers a high-quality training data set from the Web, creates a high quality lexicon, segments the training data using this lexicon and compresses the language model using the maximum likelihood principle. Expand
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Learning a semantic space from user's relevance feedback for image retrieval
TLDR
We propose spectral methods to infer a semantic space from user's relevance feedback, so that our system will gradually improve its retrieval performance through accumulated user interactions. Expand
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