Object recognition using a bio-inspired neuron model with bottom-up and top-down pathways

Author:

Zheng Yuhua,Meng Yan,Jin Yaochu

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference45 articles.

1. B. Ommer, J.M. Buhmann, Learning the compositional nature of visual objects, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2007, pp. 1–8.

2. R. Fergus, P. Perona, A. Zisserman, Object class recognition by unsupervised scale-invariant learning, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2003, pp. 264–271.

3. W. Gang, Z. Ye, F.-F. Li, Using dependent regions for object categorization in a generative framework, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006, pp. 1597–1604.

4. G. Shakhnarovich, P. Viola, T. Darrell, Fast pose estimation with parameter-sensitive hashing, in: Proceedings of the IEEE International Conference on Computer Vision, 2003, pp. 750–757.

5. Z. Hao, A.C. Berg, M. Maire, J. Malik, SVM-KNN: discriminative nearest neighbor classification for visual category recognition, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006, pp. 2126–2136.

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