SAR IMAGE CLASSIFICATION USING DEEP LEARNING

Likhitha Bhavya Billala; Lakshmi Gayathri Gudipati; Sri Vidya Bhemineni; Lakshmi Prasanna Bellamkonda; Dr. Y. Mallikarjuna Reddy

SAR IMAGE CLASSIFICATION USING DEEP LEARNING

March 2024

Vol-10, Issue-2

Paper ID: 22796

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Electronics And Communication Engineering

Keywords

GAN-Generative Adversarial Network CNN-Convolution Neural Network DL-Deep Learning MSTAR dataset Keras TensorFlow.

Abstract

This paper tackles the complex problems of low contrast and speckle noise in synthetic aperture radar (SAR) image categorization. We suggest a unique method that makes use of Generative Adversarial Networks (GANs) to create synthetic SAR images for training deep learning (DL) models, namely Convolutional Neural Networks (CNNs), by utilizing the power of DL. The CNN performs better when it comes to classifying SAR photos because the GAN is trained to produce a variety of synthetic images for various classifications. Using the MSTAR dataset, a thorough analysis shows an astounding 98.5% accuracy, proving the state-of-the-art status of our method. This shows that GANs may be used to enhance DL models in an efficient manner, opening the door to useful SAR image categorization systems that have a great deal of potential for real-world use. The frameworks TensorFlow and Keras are used in the implementation.

License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Information

#	Name	Institute / Affiliation
1	Likhitha Bhavya Billala	Vasireddy Venkatadri Institute of Technology
2	Lakshmi Gayathri Gudipati	Vasireddy Venkatadri Institute of Technology
3	Sri Vidya Bhemineni	Vasireddy Venkatadri Institute of Technology
4	Lakshmi Prasanna Bellamkonda	Vasireddy Venkatadri Institute of Technology
5	Dr. Y. Mallikarjuna Reddy	Vasireddy Venkatadri Institute of Technology

How to Cite

Use the following formats to cite this article in your research.

APA Style

Billala, Likhitha Bhavya, Gudipati, Lakshmi Gayathri, Bhemineni, Sri Vidya, Bellamkonda, Lakshmi Prasanna, & Reddy, Dr. Y. Mallikarjuna (2024). SAR IMAGE CLASSIFICATION USING DEEP LEARNING. International Journal of Advance Research and Innovative Ideas In Education, 10(2), 736-742.

MLA Style

Billala, Likhitha Bhavya, et al. "SAR IMAGE CLASSIFICATION USING DEEP LEARNING." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 2, 2024, pp. 736-742.

IEEE Style

Likhitha Bhavya Billala, Lakshmi Gayathri Gudipati, Sri Vidya Bhemineni, Lakshmi Prasanna Bellamkonda, and Dr. Y. Mallikarjuna Reddy, "SAR IMAGE CLASSIFICATION USING DEEP LEARNING," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 2, pp. 736-742, 2024.

Vancouver Style

Billala Likhitha Bhavya, Gudipati Lakshmi Gayathri, Bhemineni Sri Vidya, Bellamkonda Lakshmi Prasanna, Reddy Dr. Y. Mallikarjuna. SAR IMAGE CLASSIFICATION USING DEEP LEARNING. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(2):736-742.

Harvard Style

Billala, Likhitha Bhavya, Gudipati, Lakshmi Gayathri, Bhemineni, Sri Vidya, Bellamkonda, Lakshmi Prasanna, & Reddy, Dr. Y. Mallikarjuna (2024) 'SAR IMAGE CLASSIFICATION USING DEEP LEARNING', International Journal of Advance Research and Innovative Ideas In Education, 10(2), pp. 736-742.

Chicago Style

Billala, Likhitha Bhavya, et al. "SAR IMAGE CLASSIFICATION USING DEEP LEARNING." International Journal of Advance Research and Innovative Ideas In Education 10, no. 2 (2024): 736-742.

Turabian Style

Billala, Likhitha Bhavya, et al. "SAR IMAGE CLASSIFICATION USING DEEP LEARNING." International Journal of Advance Research and Innovative Ideas In Education 10, no. 2 (2024): 736-742.