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Computer Science > Computer Vision and Pattern Recognition

arXiv:1411.5140 (cs)
[Submitted on 19 Nov 2014]

Title:Attentional Neural Network: Feature Selection Using Cognitive Feedback

Authors:Qian Wang, Jiaxing Zhang, Sen Song, Zheng Zhang
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Abstract:Attentional Neural Network is a new framework that integrates top-down cognitive bias and bottom-up feature extraction in one coherent architecture. The top-down influence is especially effective when dealing with high noise or difficult segmentation problems. Our system is modular and extensible. It is also easy to train and cheap to run, and yet can accommodate complex behaviors. We obtain classification accuracy better than or competitive with state of art results on the MNIST variation dataset, and successfully disentangle overlaid digits with high success rates. We view such a general purpose framework as an essential foundation for a larger system emulating the cognitive abilities of the whole brain.
Comments: Poster in Neural Information Processing Systems (NIPS) 2014
Subjects: Computer Vision and Pattern Recognition (cs.CV); Neural and Evolutionary Computing (cs.NE)
Cite as: arXiv:1411.5140 [cs.CV]
  (or arXiv:1411.5140v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.1411.5140

Submission history

From: Qian Wang [view email]
[v1] Wed, 19 Nov 2014 08:33:28 UTC (2,248 KB)
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