Real-time Detection of Vehicle and Traffic Light for Intelligent and Connected Vehicles Based on YOLOv3 Network
Citations
19 citations
Cites background or methods from "Real-time Detection of Vehicle and ..."
...According to [47], YOLOV3 is an improved version of YOLOV2 with the aim to obtain a higher accuracy through the use of scales forecasts, multi-label classification prediction, and a resource extractor characteristic....
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...In [47], a method of real-time detection of vehicles and traffic...
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16 citations
11 citations
Cites background or methods from "Real-time Detection of Vehicle and ..."
...Network models such as RetinaNet [26], and YOLO [8,22] have also been studied....
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...Some leaning based methods include not only traffic light detection but also car detection [8] and approaches that recognize which lane a traffic light belongs to have been developed [10,11]....
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...Because of the rapid development of machine learning techniques, this is currently one of the most popular approaches [8,9]....
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8 citations
8 citations
References
27,256 citations
"Real-time Detection of Vehicle and ..." refers methods in this paper
...Many typical algorithms were presented after the R-CNN, such as SPPNet [4], Fast R-CNN [5], Faster R-CNN [6], R-FCN [7], FPN [8], Mask RCNN [9], SSD [10], YOLO [11], YOLOv2 [12], YOLOv3 [13] and so on....
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26,458 citations
"Real-time Detection of Vehicle and ..." refers methods in this paper
...In 2014, the R-CNN algorithm was proposed by Girshick et al, who introduced CNN for the first time in the field of objection detection....
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...Many typical algorithms were presented after the R-CNN, such as SPPNet [4], Fast R-CNN [5], Faster R-CNN [6], R-FCN [7], FPN [8], Mask RCNN [9], SSD [10], YOLO [11], YOLOv2 [12], YOLOv3 [13] and so on....
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...The YOLOv3 network has lower requirements on hardware devices than other target detection algorithms like Faster R-CNN....
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23,183 citations
19,543 citations
"Real-time Detection of Vehicle and ..." refers methods in this paper
...Many typical algorithms were presented after the R-CNN, such as SPPNet [4], Fast R-CNN [5], Faster R-CNN [6], R-FCN [7], FPN [8], Mask RCNN [9], SSD [10], YOLO [11], YOLOv2 [12], YOLOv3 [13] and so on....
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...B. YOLOv2 In view of the fact that the accuracy of YOLO is not high enough, it is easy to miss detection, and the effect of objects with uncommon long aspect ratio is poor, combined with the characteristics of SSD, YOLOv2 is proposed....
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...2) Remove the fully connected layer: Like the SSD, the model contains only the convolution and the average pooling layer....
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16,727 citations
"Real-time Detection of Vehicle and ..." refers methods in this paper
...Many typical algorithms were presented after the R-CNN, such as SPPNet [4], Fast R-CNN [5], Faster R-CNN [6], R-FCN [7], FPN [8], Mask RCNN [9], SSD [10], YOLO [11], YOLOv2 [12], YOLOv3 [13] and so on....
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