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ABSTRACT
Hyper spectral imaging (HSI) is an advanced and fascinating remote sensing method in various domains. Every sample in HS remote sensing images possesses high-size features and has a massive amount of spatial and spectral data that enhances the complexity of feature selection and mining. Also, it improves the interpretational complications and thus surpasses the prediction accuracy of the system. To counterpart such issues, this article introduces an innovative system for HSI categorization wielding introduced Fractional Snake Honey Badger Optimization (FSHBO). Here, image segmentation is done through U-Net, which is trained by Snake Honey Badger Optimization (SHBO). The Deep Belief Network (DBN) is employed for HSI classification that outputs the pixel-wise classified result and this DBN is efficiently tuned using the proposed FSHBO. It is recorded that the proposed FSHBO-DBN has outperformed diverse classical models in terms of accuracy of 0.907, sensitivity of 0.914, and specificity of 0.904.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Tatireddy Subba Reddy
Dr. Tatireddy Subba Reddy working as an Assistant Professor in the Department of Computer Science and Engineering, B V Raju Institute of Technology, Narsapur, Medak District. He received his Master's Degree from Jawaharlal Nehru Technological University (JNTU), Kakinada and Ph.D from VIT-AP University, Andhra Pradesh. He has 6 years of teaching and 4 years of research experience. He has published more than 20 research articles in various National/International Conferences/Journals. He also published one Indian patent and one text book “Deep Learning and Its applications. He has delivered experts talks at various reputed Institutions in India. He acted as a technical member and reviewer for various National/International Conferences/Journals. He has completed many global certifications on Data Science, Machine Learning, Deep Learning and blockchain technologies. His research domains are Remote Sensing and Health Informatics.
V. V. Krishna Reddy
Mr. V. V. Krishna Reddy is currently working as an Senior Assistant Professor in the Department of Information Technology, Lakireddy Bali Reddy College of Engineering (Autonomous) Mylavaram, Vijayawad. He completed a Bachelor of Technology from Acharya Nagarjuna University in 2009, Masters in Engineering from Hindustan University in 2011. He has 6 Research Publications to his credit in various International Journals and Conferences. His major focused research areas are Predictive Analytics, Cyber Security, Privacy-Preserving, Machine Learning, and Deep Learning techniques for some domain-specific problems.
R. Vijaya Kumar Reddy
Dr. R. Vijaya Kumar Reddy has obtained his B.Sc. in 2005 from Acharya Nagarjuna University, M.C.A in 2009 from JNTU, Kakinada and M.Tech Information Technology in 2011 from Vignan University and Stood University Topper and PhD Computer Science and Engineering in 2019 from Acharya Nagarjuna University. He has Total 11+ Years of Experience in Teaching and Research.
Dr. R. Vijaya Kumar Reddy started teaching in 2011 and worked as Assistant Professor in Computer Science and Engineering at Mother Theresa Educational Society Group of Institutions, Nunna in the state of Andhra Pradesh. And later worked as Assistant Professor in Electronics and Computer Engineering and Information Technology at Prasad V Potluri Siddhartha Institute of Technology from May 2012 to August 2021, worked as Associate Professor in Information Technology at Lakireddy Bali Reddy College of Engineering from August 2021 to May 2022 state of Andhra Pradesh, presently working Associate Professor in Computer Science and Engineering at Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur from May 2022.
Dr. R. Vijaya Kumar Reddy Radha published 6 Patents and He has authored 42 International Journal Publications and Conferences of which 15 are Scopus Indexed and 20 UGC Indexed. His publications have a total of 175 Google Scholar citations with h-index-7, i10 index-7. He is also rendering his services as a reviewer for two SCI/Scopus Indexed Journals. He is Life Member in ISTE, ISSE.
Chandra Sekhar Kolli
Dr. Chandra Sekhar Kolli is currently working as an Assistant Professor in the Department of Computer Science, GITAM (Deemed to be University), Visakhapatnam. He completed a Master's in Computer Applications from Andhra University in 2008, Masters in Engineering from Hindustan University in 2011, and Ph.D. in Computer Science from GITAM (Deemed to be University) in 2021. He has 21 Indexed Research Publications to his credit in various International Journals and Conferences. His major focused research areas are Predictive Analytics, Cyber Security, Privacy-Preserving, Machine Learning, and Deep Learning techniques for some domain-specific problems. He is Life Member in ISTE.
V. Sitharamulu
Dr V. Sitharamulu received the PhD degree from Acharya Nagarjuna University in 2017 and M.Tech. degree from JRN University in 2006. Presently working in the Dept. of Computer Science and Engineering, GITAM (Deemed to be University), Hyderabad, Telengana, India. His research interest includes Artificial intelligence, Machine Learning and Pattern recognition. He is a life member of CSI and member of ISTE.
Majjaru Chandrababu
Majjaru Chandrababu, is a research Scholar in the School of Information and Technology and Engineering, VIT Vellore. He is Graduated in Computer Science and Engineering and Post Graduated in Information Technology, Hyderabad. And his research area is in Cloud Security using Machine Learning Approach.