Abstract：To solve the problems of detection process with low detection accuracy and redundancy in the traditional detection method of Marine plankton by artificial features extraction, a multi module fusion single shot detector (MMFSSD) was proposed based on deep learning technology. The feature information enhancement module was proposed to add the receptive field of network without increasing the network complexity, and the downsampled image was infused into the module to enhance the lowlevel feature information of feature graph. The selective feature fusion module was further proposed to learn the weight of fusion in the network and selectively fuse features of different scales. The results of verification test show that the mean average precision values are 8070% and 3220% on PASCAL VOC and MS COCO testset, respectively. The mean average precision on PMID2019 dataset reaches 90.41%.
