Narayan Vyas

About

Narayan Vyas is an accomplished academician at Vivekananda Global University, Jaipur, India, where he is actively involved in research and development in computer science. He qualified for the NTA UGC NET & JRF in his first attempt, showcasing his academic excellence. He has extensive knowledge of the Internet of Things and Mobile Application Development and has provided training to students worldwide. He has published many articles in reputed, peer-reviewed national and international Scopus journals and conferences. Additionally, he has served as a keynote speaker and resource person for several workshops and webinars conducted in India. His research areas include Remote Sensing, the Internet of Things, Machine Learning, Deep Learning, and Computer Vision. He is an IEEE Member and active member of various International/National societies such as IEEE Young Professional, IEEE Geosciences and Remote Sensing Society (GRSS), IEEE Sensors Council, International Society of Photogrammetry and Remote Sensing (ISPRS), etc. He has 40+ publications in reputed Scopus-indexed conferences and journals and has edited 12+ books with various reputed publishers like Wiley, DeGruyter, Apple Academic Press, and IGI Global.

Employment

• Vivekananda Global University Assistant Professor
  2024 - Present
• Chandigarh University Technical Trainer
  2023 - 2024

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (43)

• Impact of Image Fusion of Optical and Microwave Satellite Imagery Under Cloudy Conditions
  IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS) 2026 DOI: 10.1109/M2GARSS67833.2026.11581999
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• Tools and Software Essential Resources for AI Integration
  2026 DOI: 10.1201/9781003616207-7
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• Land Use and Land Cover Classification in Google Earth Engine Using Sentinel-2 Based Random Forest: A Case Study of Katsina State, Nigeria
  2026 DOI: 10.2991/978-94-6239-713-2_31
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• An efficient posterior probability-based image fusion change detection model for the estimation of seasonal agricultural changes using microwave and optical datasets
  Computers and Electronics in Agriculture 2025 DOI: 10.1016/j.compag.2025.110683
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• 1Integrating Sentinel-1Sentinel-1 satellite data with machine learning for land use classification
  2025 DOI: 10.1515/9783111572970-001
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• 229Revolutionizing agricultural and environmental analytics with synthetic aperture radar (SAR): innovations, challenges, and future directions
  2025 DOI: 10.1515/9783111572970-015
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• A novel pixel-based deep neural network in posterior probability space for the detection of agriculture changes using remote sensing data
  Remote Sensing Applications: Society and Environment 2025 DOI: 10.1016/j.rsase.2025.101591
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• A novel image fusion-based post classification framework for agricultural variations detection using Sentinel-1 and Sentinel-2 data
  Earth Science Informatics 2025 DOI: 10.1007/S12145-024-01506-0
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• Evaluating the Effectiveness of Machine Learning Algorithms Using Google Earth Engine for Land Use Land Cover Classification
  Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS) 2025 DOI: 10.1109/IGARSS55030.2025.11242442
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• Leveraging sentinel-2 multispectral data and machine learning algorithms for land use land cover mapping in semi-arid regions
  International Conference on Advancement in Computation & Computer Technologies (ICACCT) 2025 DOI: 10.1109/INCACCT65424.2025.11011472
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