RESEARCH ON SEA GARBAGE DETECTION BASED ON FASTER R-CNN

WEI Bo; ZHANG Heng; WANG Fei; WANG Shuxian; YANG Yuhao; YAO Yuqing; DAI Yang

doi:DOI:10.13205/j.hjgc.202207022

Volume 40 Issue 7

Sep. 2022

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Article Navigation > ENVIRONMENTAL ENGINEERING > 2022 > 40(7): 153-158

WEI Bo, ZHANG Heng, WANG Fei, WANG Shuxian, YANG Yuhao, YAO Yuqing, DAI Yang. RESEARCH ON SEA GARBAGE DETECTION BASED ON FASTER R-CNN[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(7): 153-158. doi: DOI:10.13205/j.hjgc.202207022

Citation:

WEI Bo, ZHANG Heng, WANG Fei, WANG Shuxian, YANG Yuhao, YAO Yuqing, DAI Yang. RESEARCH ON SEA GARBAGE DETECTION BASED ON FASTER R-CNN[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(7): 153-158. doi: DOI:10.13205/j.hjgc.202207022

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RESEARCH ON SEA GARBAGE DETECTION BASED ON FASTER R-CNN

doi: DOI:10.13205/j.hjgc.202207022

1. School of Information, Shanghai Ocean University, Shanghai 201306, China;
2. Key Laboratory of Innovation in Pelagic and Polar Fisheries, Ministry of Agriculture and Rural Affairs, East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai 200090, China

Received Date: 2021-09-18
Available Online: 2022-09-02

Abstract

Abstract

Given the serious ecological damage caused by global marine garbage pollution,a sea garbage detection algorithm based on improved fast R-CNN and a method of whether the targets in the front and back frames of the video are the same target were proposed.The improved fast R-CNN algorithm improved the detection accuracy of small targets by replacing the commonly used VGG16 feature extraction network with ResNet101network and integrating it into the feature pyramid;the method to judge whether the two frames before and after the video were the same target,was to determine whether they were the same target by comparing the area,coincidence and color difference of them.The experimental results on the field shooting data showed that compared with the traditional fast R-CNN,the map value of the improved fast R-CNN in this paper was increased by 4.9%,the convergence speed of the loss curve was faster,and the detection effect in the actual detection was better;the proposed method for judging whether the two frames are the same object had a peak precision of 100% and an average accuracy of 93% in nine videos.The proposed method mainly included the following advantages:1) the improved fast R-CNN had higher accuracy in the detection of small target garbage on the sea surface;2) the algorithm code complexity of judging whether the target of the first and second frames in the video is the same target is small,making it convenient to change the judgment threshold according to the actual situation.
- improved Faster R-CNN,
- small target,
- feature pyramid,
- same target discrimination method

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References(29)

References

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