论文标题
对用于边缘计算的二元神经网络的最新进展的评论
A Review of Recent Advances of Binary Neural Networks for Edge Computing
论文作者
论文摘要
Edge Computing有望成为人工智能中下一个最热门的主题之一，因为它使各种不断发展的领域受益，例如实时无人驾驶系统，工业应用以及对隐私保护的需求。本文回顾了非常适合前端，基于边缘计算的二进制神经网络（BNN）和1位CNN技术的最新进展。我们介绍并总结了现有的工作，并根据梯度近似，量化，体系结构，损失功能，优化方法和二进制神经体系结构搜索进行分类。我们还介绍了计算机视觉和语音识别领域的应用程序，并讨论了边缘计算的未来应用。
Edge computing is promising to become one of the next hottest topics in artificial intelligence because it benefits various evolving domains such as real-time unmanned aerial systems, industrial applications, and the demand for privacy protection. This paper reviews recent advances on binary neural network (BNN) and 1-bit CNN technologies that are well suitable for front-end, edge-based computing. We introduce and summarize existing work and classify them based on gradient approximation, quantization, architecture, loss functions, optimization method, and binary neural architecture search. We also introduce applications in the areas of computer vision and speech recognition and discuss future applications for edge computing.
