In this paper, we tackle the high computational overhead of transformers for lightweight image super-resolution. (SR). Motivated by the observations of self-attention's inter-layer repetition, we ...

Abstract: Domain generalization, focusing on training neural networks that generalize well to unseen target domains, is a critical challenge in machine learning. While most existing approaches rely on ...

Abstract: We propose 3D convolution and adaptive patch-size based random patches network (RPNet), called 3DA-RPNet, for classification of hyperspectral images (HSI). Recently proposed RPNet randomly ...

Artificial intelligence is consuming enormous amounts of energy, but researchers at the University of Florida have built a chip that could change everything by using light instead of electricity for a ...

Enjoy the pain I go through so you don't have to worry about being caught cheating (hopefully) Report any bugs, issues, detections or ideas to me on Discord (NoTwistedHere#6703) or GitHub ...