Industrial Fish Classifier with Deep Artificial Neural Network
Today, machine learning-based decision support systems play a facilitating role in almost every aspect of life. With the integration of these intelligent systems into industrial production systems, fast and effective production solutions emerge. Today, machine learning-based artificial intelligence technologies mostly offer solutions based on the image processing approach. In this study, a new artificial intelligence model that can effectively classify different fish species is proposed with the YOLO image processing algorithm, a deep artificial neural network based on the image processing approach. A real-time land support solution that can be easily integrated into industrial applications is presented with the model trained with an original fish data set.
Authors
- Ersin Alaybeyoğlu
- Yasemin Erkan (ORCID: https://orcid.org/0000-0002-5825-2177)
- Mahamat Ahmat Issamadine
Institutions
- Bartin University (TR)
Publication Details
- Journal
- Orclever Proceedings of Research and Development
- Published
- 2024-12-31
- DOI
- https://doi.org/10.56038/oprd.v5i1.504
- Primary Topic
- Water Quality Monitoring Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00