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A deep learning method for traffic light status recognition
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作者 Lan Yang Zeyu He +5 位作者 Xiangmo Zhao Shan Fang Jiaqi Yuan Yixu He Shijie Li Songyan Liu 《Journal of Intelligent and Connected Vehicles》 EI 2023年第3期173-182,共10页
Real-time and accurate traffic light status recognition can provide reliable data support for autonomous vehicle decision-making and control systems.To address potential problems such as the minor component of traffic... Real-time and accurate traffic light status recognition can provide reliable data support for autonomous vehicle decision-making and control systems.To address potential problems such as the minor component of traffic lights in the perceptual domain of visual sensors and the complexity of recognition scenarios,we propose an end-to-end traffic light status recognition method,ResNeSt50-CBAM-DINO(RC-DINO).First,we performed data cleaning on the Tsinghua-Tencent traffic lights(TTTL)and fused it with the Shanghai Jiao Tong University’s traffic light dataset(S2TLD)to form a Chinese urban traffic light dataset(CUTLD).Second,we combined residual network with split-attention module-50(ResNeSt50)and the convolutional block attention module(CBAM)to extract more significant traffic light features.Finally,the proposed RC-DINO and mainstream recognition algorithms were trained and analyzed using CUTLD.The experimental results show that,compared to the original DINO,RC-DINO improved the average precision(AP),AP at intersection over union(IOU)=0.5(AP50),AP for small objects(APs),average recall(AR),and balanced F score(F1-Score)by 3.1%,1.6%,3.4%,0.9%,and 0.9%,respectively,and had a certain capability to recognize the partially covered traffic light status.The above results indicate that the proposed RC-DINO improved recognition performance and robustness,making it more suitable for traffic light status recognition tasks. 展开更多
关键词 traffic light status recognition autonomous vehicle detection transformer with improved denoising anchor boxes(DINO) Chinese urban traffic light dataset(CUTLD)
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Design of Low-power Inspection Instrument Based on RF Technology
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作者 WANG Min SU Li-hua WANG Jin-hai 《Semiconductor Photonics and Technology》 CAS 2009年第3期149-152,共4页
A design for low power consumption inspection instrument, in which the ATMega32L is used as the control core, is presented. The reader with wireless identification based on RF technology is researched and the low-cost... A design for low power consumption inspection instrument, in which the ATMega32L is used as the control core, is presented. The reader with wireless identification based on RF technology is researched and the low-cost power is studied particularly. This instrument can be used in industry fields to measure temperature, humidity, gas concentration and other specifications, so it has wide applications and is worth to be extended. 展开更多
关键词 RF address recognition status recognition intelligent inspection
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