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

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

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...

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Bibliographic Details
Main Authors: Zhu, Shien, Duong, Luan H. K., Liu, Weichen
Other Authors: School of Computer Science and Engineering
Format: Conference Paper
Language:English
Published: 2020
Subjects:
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Binary Neural Networks
Edge Devices
Online Access:https://hdl.handle.net/10356/145503

Internet

https://hdl.handle.net/10356/145503

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