Research on Bioinformatics with Sparse Feature Fusion for Object Recognition

Abstract:

Combining multiple bioinformatics such as shape and color is a challenging task in object recognition. Usually, we believe that if more different bioinformatics are considered in object recognition, then we could get better result. Bag-of-words-based image representation is one of the most relevant approaches; many feature fusion methods are based on this model. Sparse coding has attracted a considerable amount of attention in many domains. A novel sparse feature fusion algorithm is proposed to fuse multiple bioinformatics to represent the images. Experimental results show good performance of the proposed algorithm.

• Periodical: Advanced Materials Research (Volume 830)
• Pages: 485-489
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.830.485
• Online since: October 2013
• Authors: Shu Fang Wu, Jie Zhu, Zhao Feng Zhang
• Keywords: Feature Fusion, Object Recognition, Sparse Coding

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