An object detection method of underwater image based on improved Deformable-DETR
Aiming at the problem of poor object detection effect and low detection accuracy caused by complex underwater environments,an improved underwater target detection algorithm Deformable-DETR-DA is proposed based on the Deformable-DETR algorithm.Using the spatial attention module and the standard Transformer block,a DFPN block is designed to increase the depth of model,and the DFPN block is embedded into the model to improve the ability of the model to extract the deep texture information.The encoder part of the original model is improved by using attention guidance,which strengthens the aggregation ability of feature information and improves the detection ability of the model in a complex environment.For the URPC dataset,the average precision(AP)of each intersection over union scale of the model is 39.5％,which is 1％higher than the original model.Compared with some DETR-like models,the average precision of different object scales is improved by 1％～4％,which shows that the improved model can well solve the problem of underwater object detection in complex environments.The model proposed in this paper can serve as a reference for the design of other underwater object detection models.
万方数据
维普
