In this tutorial, we walk through advanced usage of Einops to express complex tensor transformations in a clear, readable, and mathematically precise way. We demonstrate how rearrange, reduce, repeat, ...

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, RandLA-Net, and VoxelRCNN— on a Flash Lidar dataset ...

The efficacy of deep residual networks is fundamentally predicated on the identity shortcut connection. While this mechanism effectively mitigates the vanishing gradient problem, it imposes a strictly ...

Abstract: Significant advancements in deep learning have been made possible by the utilization of large datasets, underscoring the critical importance of copyright protection. Adding meticulously ...

Abstract: Adversarial examples have become a critical focus in ensuring the security and robustness of deep learning (DL) systems. In this paper, we introduce an innovative approach for generating ...

Two particular phases in your nightly routine seem to play outsize roles in cognitive health. By Mohana Ravindranath A good night’s sleep isn’t just about the number of hours you log. Getting quality ...

This Collection calls for submissions of original research into techniques that facilitate the advancement of deep learning for image analysis and object detection, driving computer vision forward and ...

The application of deep learning algorithms in protein structure prediction has greatly influenced drug discovery and development. Accurate protein structures are crucial for understanding biological ...

Deep learning (DL), a subfield of artificial intelligence (AI), involves the development of algorithms and models that simulate the problem-solving capabilities of the human mind. Sophisticated AI ...