Cargando…
Class-Aware Fish Species Recognition Using Deep Learning for an Imbalanced Dataset
Fish species recognition is crucial to identifying the abundance of fish species in a specific area, controlling production management, and monitoring the ecosystem, especially identifying the endangered species, which makes accurate fish species recognition essential. In this work, the fish species...
Autores principales: | Alaba, Simegnew Yihunie, Nabi, M M, Shah, Chiranjibi, Prior, Jack, Campbell, Matthew D., Wallace, Farron, Ball, John E., Moorhead, Robert |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9658540/ https://www.ncbi.nlm.nih.gov/pubmed/36365964 http://dx.doi.org/10.3390/s22218268 |
Ejemplares similares
-
WCNN3D: Wavelet Convolutional Neural Network-Based 3D Object Detection for Autonomous Driving
por: Alaba, Simegnew Yihunie, et al.
Publicado: (2022) -
A Survey on Deep-Learning-Based LiDAR 3D Object Detection for Autonomous Driving
por: Alaba, Simegnew Yihunie, et al.
Publicado: (2022) -
Resampling Methods Improve the Predictive Power of Modeling in Class-Imbalanced Datasets
por: Lee, Paul H.
Publicado: (2014) -
The Use of Hellinger Distance Undersampling Model to Improve the Classification of Disease Class in Imbalanced Medical Datasets
por: Al-Shamaa, Zina Z. R., et al.
Publicado: (2020) -
Addressing Binary Classification over Class Imbalanced Clinical Datasets Using Computationally Intelligent Techniques
por: Kumar, Vinod, et al.
Publicado: (2022)