二值神经网络作为气味分类的柔性集成电路

2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS) Pub Date : 2020-08-16 DOI:10.1109/FLEPS49123.2020.9239529

Emre Ozer, Jedrzej Kufel, J. Biggs, James Myers, Charles Reynolds, Gavin Brown, Anjit Rana, A. Sou, C. Ramsdale, Scott White

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引用次数: 7

摘要

本文介绍了柔性衬底金属氧化物薄膜晶体管(TFT)技术中二元神经网络(BNN)硬件的发展。我们为汗液气味应用开发了BNN，该应用从检测气味的电子鼻传感器阵列获取数据，并对气味进行分类。我们展示了一个全功能的BNN柔性集成电路(FlexIC)，该电路采用$0.8 \mu \ mathm {m}$ n型金属氧化物TFT在聚酰亚胺上制造，功耗约为1mW，成为第一个用FlexIC构建的神经网络硬件。

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Binary Neural Network as a Flexible Integrated Circuit for Odour Classification

This paper presents the development of a binary neural network (BNN) hardware in metal-oxide thin film transistor (TFT) technology on a flexible substrate. We develop the BNN for a sweat odour application that takes data from an e-nose sensor array detecting odour, and classifies the odour. We demonstrate a fully functional BNN flexible integrated circuit (FlexIC) fabricated in $0.8 \mu \mathrm{m}$ n-type metal-oxide TFT on polyimide, consuming around 1mW power, which becomes the first neural network hardware built as a FlexIC.

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2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)

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