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Live Fish Species Classification in Underwater Images by Using Convolutional Neural Networks Based on Incremental Learning with Knowledge Distillation Loss

• Authors : Abdelouahid Ben Tamou; Abdesslam Benzinou; Kamal Nasreddine

Subjects: underwater image; fish recognition; deep learning

• Source: Machine Learning and Knowledge Extraction, Vol 4, Iss 3, Pp 753-767 (2022)

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A combination of learning and non-learning based method for enhancement, compression and reconstruction of underwater images.

• Authors : Nair, Rashmi S.¹ ; Domnic, Sandanam¹

• Source: Aquaculture & Fisheries (2096-1758). Mar2022, Vol. 7 Issue 2, p201-210. 10p.

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Targeted Data Augmentation and Hierarchical Classification with Deep Learning for Fish Species Identification in Underwater Images

• Authors : Abdelouahid Ben Tamou; Abdesslam Benzinou; Kamal Nasreddine

Subjects: underwater image; fish recognition; deep learning

• Source: Journal of Imaging, Vol 8, Iss 8, p 214 (2022)

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Underwater low-light image enhancement using a hybrid CNN–transformer framework with multi-scale feature fusion and cheetah optimization

• Authors : Divya Midhunchakkaravarthy; Katakam RangaNarayana; V. Lakshman Narayana

Subjects: Underwater images; Convolutional neural network; Cheetah optimization algorithm

• Source: Discover Computing, Vol 29, Iss 1, Pp 1-22 (2026)

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A Deep learning method for accurate and fast identification of coral reef fishes in underwater images

• Authors : Mouillot, David; Villon, Sébastien; Chaumont, Marc ...

Subjects: Convolutional neural network; Underwater images; Machine learning

• Source: ISSN: 1574-9541 ; Ecological Informatics ; https://hal-lirmm.ccsd.cnrs.fr/lirmm-01884005 ; Ecological Informatics, 2018, 48, pp.238-244. ⟨10.1016/j.ecoinf.2018.09.007⟩.

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Enhancement of Underwater Images by CNN-Based Color Balance and Dehazing

• Authors : Shidong Zhu; Weilin Luo; Shunqiang Duan

Subjects: underwater image; convolutional neural network; color

• Source: Electronics, Vol 11, Iss 2537, p 2537 (2022)

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Semantic Segmentation of Fish and Underwater Environments Using Deep Convolutional Neural Networks and Learned Active Contours

• Authors : Miguel Chicchon; Hector Bedon; Carlos R. Del-Blanco

Subjects: Active contour; computer vision; convolutional neural network

• Source: IEEE Access, Vol 11, Pp 33652-33665 (2023)

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An open-set framework for underwater image classification using autoencoders

• Authors : Azim Akhtarshenas; Ramin Toosi

Subjects: Fish recognition; Underwater images classification; Convolutional neural network

• Source: SN Applied Sciences, Vol 4, Iss 8, Pp 1-10 (2022)

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Delving into Underwater Image Utility: Benchmark Dataset and Prediction Model.

• Authors : Liu, Jiapeng¹ (AUTHOR); Liu, Yi² (AUTHOR); Jiang, Qiuping¹ (AUTHOR)

• Source: Remote Sensing. Jun2025, Vol. 17 Issue 11, p1906. 20p.

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Improvement and Optimization of Underwater Image Target Detection Accuracy Based on YOLOv8.

• Authors : Sun, Yisong¹ (AUTHOR); Chen, Wei^1,2 (AUTHOR) ; Wang, Qixin¹ (AUTHOR)

• Source: Symmetry (20738994). Jul2025, Vol. 17 Issue 7, p1102. 23p.

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