State-of-the-art deep convolutional neural networks fail to accurately predict primate visual behavior at the resolution of individual images, indicating a need for improved mechanistic models of primate vision.
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Angie Rogers (2000) studied Visual object recognition (n=1,477). Deep convolutional artificial neural networks (DCNN_IC models) vs. Primate behavior (humans and macaque monkeys) was evaluated on Behavioral performance for individual images within each object discrimination task.
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