Guang-Nan He

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The “semantic gap” problem is one of the main difficulties in image retrieval tasks. Semi-supervised learning, typically integrated with the relevance feedback techniques, is an effective method to narrow down the semantic gap. However, in semi-supervised learning, the amount of unlabeled data is usually much greater than that of labeled data. Therefore,(More)
This paper presents a novel approach for image region segmentation based on color coherence quantization. Firstly, we conduct an unequal color quantization in the HSI color space to generate representative colors, each of which is used to identify coherent regions in an image. Next, all pixels are labeled with the values of their representative colors to(More)
The "semantic gap" problem is one of the main difficulties in image retrieval task. Semi-supervised learning is an effective methodology proposed to narrow down the gap, which is also often integrated with relevance feedback techniques. However, in semi-supervised learning, the amount of unlabeled data is usually much greater than that of labeled data.(More)
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