DUO

Aiming at the problem of low underwater recognition accuracy caused by dense and fuzzy targets in underwater target detection, an underwater target detection algorithm combining attention mechanism and downsampling is proposed.For the experimental evaluation, the DetectingUnderwater Objects (DUO) dataset was used,which was collected and re-annotated based onthe corresponding dataset. The dataset containsa total of 7782 images, including 6671 images fortraining and 1111 images for testing. The totalnumber of targets in the dataset is 74,515, ofwhich the number of holothurians, echinus, scal?lops, and starfish are 7,887, 50,156, 1,924, and14,548, respectively.

针对水下目标检测中目标密集模糊导致识别精度偏低的问题，本文提出一种融合注意力机制与下采样的水下目标检测算法。为开展实验评估，本研究采用了基于相关数据集采集并重新标注的水下目标检测（DetectingUnderwater Objects, DUO）数据集。该数据集共计包含7782张图像，其中训练集含6671张图像，测试集含1111张图像。数据集内目标总数量为74515个，其中海参、海胆、扇贝、海星的数量分别为7887、50156、1924以及14548个。