Smart scissor: coupling spatial redundancy reduction and CNN compression for embedded hardware

• المؤلفون الرئيسيون: Kong, Hao, Liu, Di, Huai, Shuo, Luo, Xiangzhong, Liu, Weichen, Subramaniam, Ravi, Makaya, Christian, Lin, Qian
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Computer science and engineering; Convolutional Neural Networks
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/164833
• المؤسسة: Nanyang Technological University

Scaling down the resolution of input images can greatly reduce the computational overhead of convolutional neural networks (CNNs), which is promising for edge AI. However, as an image usually contains much spatial redundancy, e.g., background pixels, directly shrinking the whole image will lose impo...