Light-induced perovskite dynamic transformation enabling photodetector mimicking neuromorphic vision sensing system

2022 ◽  
Author(s):  
Yousheng Zou ◽  
Yuqing Song ◽  
Xiaobao Xu ◽  
Yuanzhou Zhang ◽  
Zeyao Han ◽  
...  
Keyword(s):  
Neural Network ◽  
Vision Sensing ◽  
Sensing System ◽  
Image Sensing ◽  
Dynamic Transformation ◽  
Complex Image ◽  
Perception System ◽  
Neuromorphic Vision

As an artificial perception system, neuromorphic vision sensing system can imitate the complex image sensing and processing functions of the human visual neural network. In order to stimulate the nervous...

scholarly journals Implementation of Multi-Exit Neural-Network Inferences for an Image-Based Sensing System with Energy Harvesting

2021 ◽  
Vol 11 (3) ◽  
pp. 34
Author(s):  
Yuyang Li ◽  
Yuxin Gao ◽  
Minghe Shao ◽  
Joseph T. Tonecha ◽  
Yawen Wu ◽  
...  
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Memory Storage ◽  
Wireless Sensor ◽  
Energy Capacity ◽  
Embedded Platform ◽  
Sensing System ◽  
Image Sensing ◽  
Space Limitation ◽  
Battery Energy

Wireless sensor systems powered by batteries are widely used in a variety of applications. For applications with space limitation, their size was reduced, limiting battery energy capacity and memory storage size. A multi-exit neural network enables to overcome these limitations by filtering out data without objects of interest, thereby avoiding computing the entire neural network. This paper proposes to implement a multi-exit convolutional neural network on the ESP32-CAM embedded platform as an image-sensing system with an energy constraint. The multi-exit design saves energy by 42.7% compared with the single-exit condition. A simulation result, based on an exemplary natural outdoor light profile and measured energy consumption of the proposed system, shows that the system can sustain its operation with a 3.2 kJ (275 mAh @ 3.2 V) battery by scarifying the accuracy only by 2.7%.

scholarly journals A flexible ultrasensitive optoelectronic sensor array for neuromorphic vision systems

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Qian-Bing Zhu ◽  
Bo Li ◽  
Dan-Dan Yang ◽  
Chi Liu ◽  
Shun Feng ◽  
...  
Keyword(s):  
Sensor Array ◽  
Vision System ◽  
Vision Systems ◽  
Neuromorphic Circuits ◽  
Image Sensing ◽  
Perovskite Quantum Dots ◽  
Optoelectronic Sensor ◽  
Weak Light ◽  
Do So ◽  
Neuromorphic Vision

AbstractThe challenges of developing neuromorphic vision systems inspired by the human eye come not only from how to recreate the flexibility, sophistication, and adaptability of animal systems, but also how to do so with computational efficiency and elegance. Similar to biological systems, these neuromorphic circuits integrate functions of image sensing, memory and processing into the device, and process continuous analog brightness signal in real-time. High-integration, flexibility and ultra-sensitivity are essential for practical artificial vision systems that attempt to emulate biological processing. Here, we present a flexible optoelectronic sensor array of 1024 pixels using a combination of carbon nanotubes and perovskite quantum dots as active materials for an efficient neuromorphic vision system. The device has an extraordinary sensitivity to light with a responsivity of 5.1 × 107 A/W and a specific detectivity of 2 × 1016 Jones, and demonstrates neuromorphic reinforcement learning by training the sensor array with a weak light pulse of 1 μW/cm2.

scholarly journals A Performance Prediction Method Based on Sliding Window Grey Neural Network for Inertial Platform

2021 ◽  
Vol 13 (23) ◽  
pp. 4864
Author(s):  
Langfu Cui ◽  
Qingzhen Zhang ◽  
Liman Yang ◽  
Chenggang Bai
Keyword(s):  
Neural Network ◽  
Prediction Models ◽  
Prediction Method ◽  
Sliding Window ◽  
Small Sample ◽  
Grey Theory ◽  
Sensing System ◽  
Performance Change ◽  
Sample Data ◽  
Platform System

An inertial platform is the key component of a remote sensing system. During service, the performance of the inertial platform appears in degradation and accuracy reduction. For better maintenance, the inertial platform system is checked and maintained regularly. The performance change of an inertial platform can be evaluated by detection data. Due to limitations of detection conditions, inertial platform detection data belongs to small sample data. In this paper, in order to predict the performance of an inertial platform, a prediction model for an inertial platform is designed combining a sliding window, grey theory and neural network (SGMNN). The experiments results show that the SGMNN model performs best in predicting the inertial platform drift rate compared with other prediction models.

Visual Sensing System for Thin Plate Welding Based on Rotund Facular Laser

2012 ◽  
Vol 538-541 ◽  
pp. 1498-1501
Author(s):  
Wang Ping Gu ◽  
Zhen Yu Xiong ◽  
Pin Liu
Keyword(s):  
Thin Plate ◽  
Visual Image ◽  
Sensor System ◽  
Vision Sensor ◽  
Butt Welding ◽  
Vision Sensing ◽  
Sensing System ◽  
Visual Sensing ◽  
Processing Software ◽  
Image Processing Software

In order to solve the problem of thin plate butt-welded tracking, a welding vision sensing system with a rotund facular laser has been designed. In the vision sense system, each parameter of the interior part has been designed by a variety of experiments. The designed image processing software can precisely identify the position of the joint, based on the optimal designed vision sensor system. The thin plate butt welding experiments have been taken with the designed sensing device. The experimental results show that the vision sensor system with a suitable auxiliary illuminant can obtain satisfying visual image information in stainless thin plate butt-welded.

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