MCR-YOLO model for underwater target detection based on multi-color spatial features

Author:

Liu Peiyu,Xing Weiwei,Ma Yixuan

Publisher

Springer Science and Business Media LLC

Reference22 articles.

1. ZHANG S, WANG T, DONG J, et al. Underwater image enhancement via extended multi-scale retinex[J]. Neuro computing, 2017, 245: 1–9.

2. REN S, HE K, GIRSHICK R, et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE transactions on pattern analysis and machine intelligence, 2017, 39(6): 1137–1149.

3. BOCHKOVSKIY A, WANG C Y, LIAO H Y M. YOLOv4: optimal speed and accuracy of object detec-tion[EB/OL]. (2020-04-23) [2022-10-17]. https://arxiv.org/abs/2004.10934.

4. ANCUTI C O, ANCUTI C, VLEESCHOUWER C D, et al. Color balance and fusion for underwater image enhancement[J]. IEEE transactions on image processing, 2018, 27(1): 379–393.

5. LIN W H, ZHONG J X, LIU S, et al. RoIMix: proposal-fusion among multiple images for underwater object detection[C]//IEEE International Conference on Acoustics, Speech and Signal Processing, May 4–8, 2020, Barcelona, Spain. New York: IEEE, 2020: 2588–2592.

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