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Found 4 papers, 2 papers with code
Human Eyes Inspired Recurrent Neural Networks are More Robust Against Adversarial Noises
Compared to human vision, computer vision based on convolutional neural networks (CNN) are more vulnerable to adversarial noises.
Explainable Semantic Space by Grounding Language to Vision with Cross-Modal Contrastive Learning
After training, the language stream of this model is a stand-alone language model capable of embedding concepts in a visually grounded semantic space.
Deep Predictive Coding Network with Local Recurrent Processing for Object Recognition
When unfolded over time, the recurrent processing gives rise to an increasingly deeper hierarchy of non-linear transformation, allowing a shallow network to dynamically extend itself into an arbitrarily deep network.
Deep Predictive Coding Network for Object Recognition
Given image input, PCN runs recursive cycles of bottom-up and top-down computation to update its internal representations and reduce the difference between bottom-up input and top-down prediction at every layer.
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