卷积神经网络
感知
神经形态工程学
人工智能
灵敏度(控制系统)
神经科学
计算机视觉
鉴定(生物学)
深度学习
领域(数学)
计算机科学
人机交互
人工神经网络
电子工程
工程类
植物
数学
纯数学
生物
作者
Yan Du,Penghui Shen,Houfang Liu,Yuyang Zhang,Luyao Jia,Xiong Pu,Feiyao Yang,Tian‐Ling Ren,Daping Chu,Zhong Lin Wang,Di Wei
出处
期刊:Science Advances
[American Association for the Advancement of Science (AAAS)]
日期:2024-09-11
卷期号:10 (37)
标识
DOI:10.1126/sciadv.adp8681
摘要
The limitations and complexity of traditional noncontact sensors in terms of sensitivity and threshold settings pose great challenges to extend the traditional five human senses. Here, we propose tele-perception to enhance human perception and cognition beyond these conventional noncontact sensors. Our bionic multi-receptor skin employs structured doping of inorganic nanoparticles to enhance the local electric field, coupled with advanced deep learning algorithms, achieving a Δ V /Δ d sensitivity of 14.2, surpassing benchmarks. This enables precise remote control of surveillance systems and robotic manipulators. Our long short-term memory–based adaptive pulse identification achieves 99.56% accuracy in material identification with accelerated processing speeds. In addition, we demonstrate the feasibility of using a two-dimensional (2D) sensor matrix to integrate real object scan data into a convolutional neural network to accurately discriminate the shape and material of 3D objects. This promises transformative advances in human-computer interaction and neuromorphic computing.
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