XOR-Net : an efficient computation pipeline for binary neural network inference on edge devices

• Main Authors: Zhu, Shien, Duong, Luan H. K., Liu, Weichen
• 其他作者: School of Computer Science and Engineering
• 格式: Conference or Workshop Item
• 語言: English
• 出版: 2020
• 主題: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence; Binary Neural Networks; Edge Devices
• 在線閱讀: https://hdl.handle.net/10356/145503; https://doi.org/10.21979/N9/XEH3D1
• 機構: Nanyang Technological University

Accelerating the inference of Convolution Neural Networks (CNNs) on edge devices is essential due to the small memory size and poor computation capability of these devices. Network quantization methods such as XNOR-Net, Bi-Real-Net, and XNOR-Net++ reduce the memory usage of CNNs by binarizing the CN...