Understanding the species composition,abundance and temporal and spatial distribution of fish on a global scale will help their biodiversity conservation.Underwater image acquisition is one of the main means to survey fish species diversity,but image data analysis is time-consuming and labor-intensive.Since 2015,a series of progress has been made in updating the datasets of marine fish images and optimizing the algorithm of deep learning models,but the performance of fine-grained classification is still insufficient,and the production practice application of research results is relatively weak.Therefore,the need for automated fish image classification in marine investigations is firstly studied.Then a comprehensive introduction to fish image datasets and deep learning algorithm applications is provided,and the main challenges and the corresponding solutions are analyzed.Finally,the importance of automated classification of marine fish images for related image information processing research is discussed,and its prospects in the field of marine monitoring are summarized.
关键词
深度学习/海洋鱼类/生物多样性/小样本/图像分类
Key words
Deep learning/Marine fish/Biodiversity/Few shots/Image classification
维普
万方数据