FishRNFuseNET: development of heuristic-derived recurrent neural network with feature fusion strategy for fish species classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software
Link
https://link.springer.com/content/pdf/10.1007/s10115-023-01987-3.pdf
Reference47 articles.
1. Allken V, Handegard NO, Rosen S, Schreyeck T, Mahiout T, Malde K (2019) Fish species identification using a convolutional neural network trained on synthetic data. ICES J Mar Sci 76(1):342–349
2. Anderson Aparecido dos Santos AA, Gonçalves WN (2019) Improving pantanal fish species recognition through taxonomic ranks in convolutional neural networks. Ecol Inform 53.
3. Jalal A, Salman A, Mian A, Shortis M, Shafait F (2020) Fish detection and species classification in underwater environments using deep learning with temporal information. Ecol Inform 57.
4. Jin L, Liang H (2017) Deep learning for underwater image recognition in small sample size situations. OCEANS, pp 1–4.
5. Li X, Shang M, Qin H, Chen L (2015) Fast accurate fish detection and recognition of underwater images with fast r-cnn. OCEANS, pp 1–5.
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