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Research Article

An Ingenious System to Predict Rock Vs Mine by Sonar Using Logistic Regression

G. Rajeswari1 J.V. Kowsalya2 T.S. Navalakshmi3
1Assistant Professor, Department of Computer Science and Engineering, K.L.N. College of Engineering, Sivagangai, Tamilnadu, India. 23Final Year Students, Department of Computer Science and Engineering, K.L.N. College of Engineering, Sivagangai, Tamilnadu, India.

Published Online: September-October 2024

Pages: 34-36

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References

[1]. The paper titled “Application of Machine Learning Algorithms for Classification of Mines and Rocks Using Sonar Data” (2024) by
Abhishek Kumar and Sanjay Kumar Soni investigates the application of various machine learning algorithmsto classify sonar
readings collected from underwater mines and rocks.
[2]. “Mine Detection and Classification using Neural Networks” by R. Todd Moon and W. Dale Blair explores the utilization of neural
networks models for the identification of landmines using ground-penetrating radar (GPR) signals.
[3]. “Classification of Underwater Objects using Neural Networks and Spectral Analysis” by Kalyanmoy Deb and S. Sanyal.
[4]. “Side-scan Sonar Imaging Data of Underwater Vehicles for Mine Detection” (vol 53, 2024) by Nuno Pessanha Santos, Ricardo
Moura, Goncalo Sampaio Torgal, Victor Lobo, and Miiguel de Castro NetoSide.
[5]. Sri Ramya Yaramasu, Uppada Sai Gayatri, Vadlamani Manjusha, Vaishna C Bhanu, Koda Indu.“UNDERWATER MINE
& ROCK PREDICTION BY EVALUATION OF,” (2016)
[6]. Stanislaw Ho˙zy´n. “A Review of Underwater Mine Detection and Classification in Sonar Imagery.” (2021).

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