Brain-Inspired Attention Model for Object Counting
Sequential visual attention and reinforcement learning for accurate object counting.
Authors: Abhijeet Sinha, Sweta Kumari, and V. Srinivasa Chakravarthy
Venue: International Conference on Neural Information Processing (ICONIP), 2023
This work presents a brain-inspired sequential attention model that uses Q-learning and recurrent visual glimpses for object counting. By learning where to look and integrating information across glimpses, the model achieved 92.1% object-counting accuracy.