Towards More Efficient EfficientDets and Real-Time Marine Debris Detection

Federico Zocco, Tzu Chieh Lin, Ching I. Huang, Hsueh Cheng Wang, Mohammad Omar Khyam, Mien Van*


研究成果: Article同行評審

3 引文 斯高帕斯(Scopus)


Marine debris is a problem both for the health of marine environments and for the human health since tiny pieces of plastic called 'microplastics' resulting from the debris decomposition over the time are entering the food chain at any levels. For marine debris detection and removal, autonomous underwater vehicles (AUVs) are a potential solution. In this letter, we focus on the efficiency of AUV vision for real-time marine debris detection. First, we improved the efficiency of a class of state-of-the-art object detectors, namely EfficientDets [1], by 1.5% AP on D0, 2.6% AP on D1, 1.2% AP on D2 and 1.3% AP on D3 without increasing the GPU latency (see Fig. 1). Subsequently, we created and made publicly available a dataset for the detection of in-water plastic bags and bottles and trained our improved EfficientDets on this and on two public datasets for marine debris detection. Finally, we began the testing of real-time detection performance on a simulator of marine environments.

頁(從 - 到)2134-2141
期刊IEEE Robotics and Automation Letters
出版狀態Published - 1 4月 2023


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