SATELLITE IMAGE CLASSIFICATION: A DEEP LEARNING APPROACH USING MOBILENETV2

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{182947,
        author = {NANDHIPATI SWATHI and DR. N SRI HARI and DR. RAMACHANDRAN VEDANTAM},
        title = {SATELLITE IMAGE CLASSIFICATION: A DEEP LEARNING APPROACH USING MOBILENETV2},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {2},
        pages = {3856-3862},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=182947},
        abstract = {},
        keywords = {Satellite Image Classification, MobileNetV2, Deep Learning, Remote Sensing, Land Cover Mapping, CNN.},
        month = {July},
        }

Cite This Article

SWATHI, N., & HARI, D. N. S., & VEDANTAM, D. R. (2025). SATELLITE IMAGE CLASSIFICATION: A DEEP LEARNING APPROACH USING MOBILENETV2. International Journal of Innovative Research in Technology (IJIRT), 12(2), 3856–3862.

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