Turkish Journal of Computer and Mathematics Education
Journal license

Journal

Turkish Journal of Computer and Mathematics Education


Volume
& Issue

Volume 13, Issue 1


Published
on


Pages

85-99


DOI

Article

Image processing Model with Deep Learning Approach for Fish Species Classification


Authors

Nishq Poorav Desai* Affiliation:
Research Scholar, Vellore Institute of Technology Bhopal University, Bhopal, 466114, India
, Mohammed Farhan Balucha Affiliation:
Research Scholar, Vellore Institute of Technology Bhopal University, Bhopal, 466114, India
, Akshara Makrariya Affiliation:
Assistant Professor, Vellore Institute of Technology Bhopal University, Bhopal, 466114, India
and Rabia Musheer Aziz Affiliation:
Assistant Professor, Vellore Institute of Technology Bhopal University, Bhopal, 466114, India


Abstract

Fish image classification is seemingly simple yet a convoluted process. Moreover, the scientific research of population counts and geographical behaviour is substantial for progressing the current developments in this field. We've tried several approaches to find the optimum-performing approach using advanced computer vision and data mining techniques with limited research scope and difficulties. Its performance was compared to the state -of-art models like CNN, EfficientNet etc., to validate the credibility of the proposed model. Eventually, it was observed that the empirical approach using the ANN confirmed the DNN model to be the leading model with an accuracy of 100%.


Keywords

Image Processing, ResNet, EfficientNet, Deep Learning model, Fish Image Classification, Feature Extraction, Convolutional Neural Network


Citation

Desai, N. P., Balucha, M. F., Makrariya, A., & Aziz, R. M. (2022). Image processing model with deep learning approach for fish species classification. Turkish Journal of Computer and Mathematics Education, 13(1), 85–99.

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