Web: http://arxiv.org/abs/2206.10589

Sept. 26, 2022, 1:14 a.m. | Muhammad Maaz, Abdelrahman Shaker, Hisham Cholakkal, Salman Khan, Syed Waqas Zamir, Rao Muhammad Anwer, Fahad Shahbaz Khan

cs.CV updates on arXiv.org arxiv.org

In the pursuit of achieving ever-increasing accuracy, large and complex
neural networks are usually developed. Such models demand high computational
resources and therefore cannot be deployed on edge devices. It is of great
interest to build resource-efficient general purpose networks due to their
usefulness in several application areas. In this work, we strive to effectively
combine the strengths of both CNN and Transformer models and propose a new
efficient hybrid architecture EdgeNeXt. Specifically in EdgeNeXt, we introduce
split depth-wise transpose …

applications architecture arxiv cnn mobile transformer transformer architecture vision

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