Results 1 to 10 of about 120,659,477 (285)

Visualized in-sensor computing [PDF]

Nature Communications
In artificial nervous systems, conductivity changes indicate synaptic weight updates, but they provide limited information compared to living organisms.
Yao Ni, Jiaqi Liu, Hong Han, Qianbo Yu, Lu Yang, Zhipeng Xu, Chengpeng Jiang, Lu Liu, Wentao Xu   +8 more
doaj   +4 more sources

Optoelectronic Devices for In-Sensor Computing [PDF]

Advanced Materials
Abstract The demand for accurate perception of the physical world leads to a dramatic increase in sensory nodes. However, the transmission of massive and unstructured sensory data from sensors to computing units poses great challenges in terms of power‐efficiency, transmission bandwidth, data storage, time latency, and security.
Jianmin Yan, Yang Chai, Chaoyi Zhu
exaly   +4 more sources

Photon-efficient camera with in-sensor computing [PDF]

Nature Communications
Image sensors with internal computing capabilities fuse sensing and computing to significantly reduce the power consumption and latency of machine vision tasks.
Yanqiu Guan, Haochen Li, Yi Zhang, Yuchen Qiu, Labao Zhang, Xiangyang Ji, Hao Wang, Qi Chen, Liang Ma, Xiaohan Wang, Zhuolin Yang, Xuecou Tu, Qingyuan Zhao, Xiaoqing Jia, Jian Chen, Lin Kang, Peiheng Wu   +16 more
doaj   +4 more sources

Perovskite-Based Memristor with 50-Fold Switchable Photosensitivity for In-Sensor Computing Neural Network [PDF]

Nanomaterials, 2022
In-sensor computing can simultaneously output image information and recognition results through in-situ visual signal processing, which can greatly improve the efficiency of machine vision.
Qilai Chen, Tingting Han, Jianmin Zeng, Zhilong He, Yulin Liu, Jinglin Sun, Minghua Tang, Zhang Zhang, Pingqi Gao, Gang Liu   +9 more
doaj   +2 more sources

Capacitive in-sensor tactile computing

Nature Communications
Real-time sensing and processing of tactile information are essential to enhance the capability of artificial electronic skins (e-skins), enabling unprecedented intelligent applications in tactile exploration and object manipulation.
Yan Chen, Jie Cao, Jie Qiu, Dongzi Yang, Mengyang Liu, Mengru Zhang, Chenyang Li, Zhongyuan Wu, Jie Yu, Xumeng Zhang, Xianzhe Chen, Zhangcheng Huang, Enming Song, Ming Wang, Qi Liu, Ming Liu   +15 more
doaj   +3 more sources

Massively parallel in-sensor skinomorphic computing

Nature Communications
Real-time sensing and processing of a large amount of tactile information is essential for intelligent robotics and wearable technology. However, physical separation between sensors and processors in the traditional tactile sensing scheme makes these ...
Yixiang Li, Yuekun Yang, Cong Wang, Yitong Dai, Xiunan Yan, Dehe Kong, Zhengwei Liao, Shuang Wang, Gong-Jie Ruan, Pengfei Wang, Bin Cheng, Shi-Jun Liang, Feng Miao   +12 more
doaj   +4 more sources

In‐Sensor Reservoir Computing Based on Optoelectronic Synapse

Advanced Intelligent Systems, 2023
Conventional machine vision systems suffer from great data latency and energy consumption in cognitive tasks due to the separated vision sensors, memory units, and processors.
Yi Sun, Qingjiang Li, Xi Zhu, Cen Liao, Yongzhou Wang, Zhiwei Li, Sen Liu, Hui Xu, Wei Wang   +8 more
doaj   +1 more source

In-Sensor Visual Perception and Inference

Intelligent Computing, 2023
Conventional machine vision systems have separate perception, memory, and processing architectures, which may exacerbate the increasing need for ultrahigh image processing rates and ultralow power consumption.
Yanan Liu, Rui Fan, Jianglong Guo, Hepeng Ni, Muhammad Usman Maqboo Bhutta   +4 more
doaj   +1 more source

Artificial Multisensory Neurons with Fused Haptic and Temperature Perception for Multimodal In‐Sensor Computing

Advanced Intelligent Systems, 2022
The human receives and transmits various information from the outside world through different sensory systems. The sensory neurons integrate various sensory inputs into a synthetical perception to monitor complex environments, and this fundamentally ...
Qingxi Duan, Teng Zhang, Chang Liu, Rui Yuan, Ge Li, Pek Jun Tiw, Ke Yang, Chen Ge, Yuchao Yang, Ru Huang   +9 more
doaj   +1 more source

Cost-Reliability Tradeoffs in Fusing Unreliable Computational Units

IEEE Open Journal of Signal Processing, 2020
We investigate fusing several unreliable computational units that perform the same task. We model an unreliable computational outcome as an additive perturbation to its error-free result in terms of its fidelity and cost.
Mehmet A. Donmez, Maxim Raginsky, Andrew C. Singer, Lav R. Varshney   +3 more
doaj   +1 more source