Future Trends and Short-Review on Fish Species Classification Models Based on Deep Learning Approaches-Reference-Cited by-同舟云学术

Future Trends and Short-Review on Fish Species Classification Models Based on Deep Learning Approaches

Published:2022-11-24 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)
language:
Short-container-title:

Author:

Bhanumathi M.¹,Arthi B.²

Affiliation:

1. SRM Institute of Science and Technology,Department of Computer Science and Engineering

2. College of Engineering and Technology, SRM Institute of Science and Technology,Faculty of Engineering and Technology,Department of Computer Science and Engineering

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10010702/10010572/10011087.pdf?arnumber=10011087

Reference21 articles.

1. Naive Bayesian fusion based deep learning networks for multisegmented classification of fishes in aquaculture industries;abinaya;Ecological Informatics,2021

2. Automatic underwater fish species classification with limited data using few-shot learning

3. Carp-DCAE: Deep convolutional autoencoder for carp fish classification

4. Transfer learning and SE-ResNet152 networks-based for small-scale unbalanced fish species identification

5. Visual features based automated identification of fish species using deep convolutional neural networks

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1. Detecting Fish Species Through Mask RCNN;2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE);2024-02-22

2. Automatic Identification of Fish Species using Machine Learning;2023 OITS International Conference on Information Technology (OCIT);2023-12-13