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Weakly Supervised Underwater Fish Segmentation Using Affinity LCFCN
Estimating fish body measurements like length, width, and mass has received considerable research due to its potential in boosting productivity in marine and aquaculture applications. Some methods are based on manual collection of these measurements using tools like a ruler which is time consuming and labour intensive. Others rely on fully-supervised segmentation models to automatically acquire these measurements but require collecting per-pixel labels which are also time consuming. It can takedoi:10.21203/rs.3.rs-253336/v1 fatcat:6suge53fa5dddhrxpsxwf7swn4