Abstract：Based on the previous attention selection model with visual memory as top-down guidance, a visual memory model is put forward with online learning and forgetting, called amnesic incremental hierarchical discriminant regression (AIHDR) tree, to mimic human short-term memory (STM) and long-term memory (LTM). A self-supervised competition neural network (SSCNN) combines the information from both bottom-up and top-down to find out the focus of attention (FoA). The connection weights in SSCNN can be updated in real-time according to the environment. Experimental results show that the proposed model can mimic the shift of human attention and stare at an interesting object consciously when environment changes.
过晨雷，张立明. 带有遗忘的视觉记忆模型及其在注意力选择上的应用*[J]. 模式识别与人工智能, 2008, 21(3): 381-387.
GUO Chen-Lei, ZHANG Li-Ming. A Visual Memory Model with Amnesic Function and Its Application in Attention Selection. , 2008, 21(3): 381-387.
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