Automatic recognition and classification of microalgae using an inception-v3 convolution neural network model
Author:
Funder
National Key R&D Program of China
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
General Agricultural and Biological Sciences,Environmental Chemistry,Environmental Engineering
Link
https://link.springer.com/content/pdf/10.1007/s13762-023-05209-9.pdf
Reference36 articles.
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2. Chong JWR, Khoo KS, Chew KW, Ting HY, Show PL (2023) Trends in digital image processing of isolated microalgae by incorporating classification algorithm. Biotechnol Adv 63:108095. https://doi.org/10.1016/j.biotechadv.2023.108095
3. Coltelli P, Barsanti L, Evangelista V, Frassanito AM, Passarelli V, Gualtieri P (2013) Automatic and real time recognition of microalgae by means of pigment signature and shape. Environ Sci Process Impacts 15(7):1397–1410. https://doi.org/10.1039/C3EM00160A
4. Correa I, Drews P, Botelho S, de Souza MS, Tavano VM (2017) Deep learning for microalgae classification. In: 2017 16th IEEE international conference on machine learning and applications (ICMLA). pp 20–25
5. Deng J, Dong W, Socher R, Li LJ, Li FF (2009) Imagenet: a large-scale hierarchical image database. In: 2009 IEEE Computer society conference on computer vision and pattern recognition (CVPR 2009), 20–25 June 2009, Miami, Florida, USA
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