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Found 3 papers, 2 papers with code
MHSAN: Multi-Head Self-Attention Network for Visual Semantic Embedding
Thus, in addition to the joint embedding space, we propose a novel multi-head self-attention network to capture various components of visual and textual data by attending to important parts in data.
Generation of 3D Brain MRI Using Auto-Encoding Generative Adversarial Networks
We also train the model to synthesize brain disorder MRI data to demonstrate the wide applicability of our model.
Representation of White- and Black-Box Adversarial Examples in Deep Neural Networks and Humans: A Functional Magnetic Resonance Imaging Study
However, DNNs exhibit idiosyncrasies that suggest their visual representation and processing might be substantially different from human vision.
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