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About Marine Animal Detection and Recognition With Advanced Deep Learning Models
This document summarizes the authors' contributions to three tasks in SEACLEF-2017 involving automatic detection and recognition of marine animals from images and video. For task 1 on fish species recognition, they used SSD and PVANET models to detect bounding boxes around fish, then classified the boxes using a ResNet-10 network. For task 2 on salmon identification, they used a BN-Inception network to classify frames as containing salmon or not. For task 3 on weakly-labeled marine animal recognition, they examined various neural networks for classification. Their methods achieved good results in tasks 1 and 3.
Detailed Information
Author: | ['Anh Minh Tran'] |
---|---|
Publication Year: | 2021 |
Pages: | 9 |
Language: | English |
Format: | |
Price: | FREE |
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