Incremental Hierarchical Discriminant Regression for Online Image Classification
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Democratic Integration: Self-Organized Integration of Adaptive Cues
Neural Computation
A context-dependent attention system for a social robot
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Attention Selection with Self-supervised Competition Neural Network and Its Applications in Robot
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
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In this paper an attention selection system based on neural network is proposed, which combines supervised and unsupervised learning reasonably. A value system and memory tree with update ability are regarded as teachers to adjust the weights of neural network. Both bottom-up and top-down part are to simulate two-stage hypothesis of attention selection in biological vision. The system is able to track objects that it is interested in. Whenever it lost focus on tracked object, it can find the object again in a short time.