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Bappa Das
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- 2026
[j7]Abhradip Sarkar, Pragati Pramanik Maity, Fitsum T. Teshome, V. K. Sehgal, Alka Arora, Md. Ashraful Haque, Bappa Das, Mrinmoy Ray, Siddhartho Shekhar Paul
:
Integration of smartphone imagery with topographic parameters for soil organic carbon prediction in the Indo-Gangetic Plains: an interpretable machine learning approach. Comput. Electron. Agric. 241: 111279 (2026)
[j6]Shagun Jain
, Divyashikha Sethia
, Kailash Chandra Tiwari
, Bappa Das
, Parveen Kumar
, Gopal Ramdas Mahajan:
ExGAPS: A unified and optimized explainable AI-driven framework for multivariate hyperspectral soil property estimation. Eng. Appl. Artif. Intell. 170: 114257 (2026)- 2025
[j5]Bhabani Prasad Mondal, Rabi Narayan Sahoo, Bappa Das, Nayan Ahmed, Kali Kinkar Bandyopadhyay, Joydeep Mukherjee, Alka Arora, Ali Refaat Ali Moursy:
Digital mapping of DTPA extractable micronutrients using combined AVIRIS-NG hyperspectral and multispectral data of Sentinel-2 and SRTM-DEM. Comput. Electron. Agric. 239: 110905 (2025)
[j4]Justin George Kalambukattu
, Suresh Kumar, Bappa Das, Trisha Roy:
Soil depth mapping in the hilly and mountainous landscape of North-West Himalayan region using machine learning technique. Earth Sci. Informatics 18(3): 492 (2025)- 2023
[j3]RN Singh, Prameela Krishnan
, C. Bharadwaj, Bappa Das
:
Improving prediction of chickpea wilt severity using machine learning coupled with model combination techniques under field conditions. Ecol. Informatics 73: 101933 (2023)
[j2]Abhradip Sarkar, Pragati Pramanik Maity, Mrinmoy Ray
, Debashis Chakraborty, Bappa Das
, Arti Bhatia:
Inclusion of fractal dimension in four machine learning algorithms improves the prediction accuracy of mean weight diameter of soil. Ecol. Informatics 74: 101959 (2023)- 2021
[j1]Gopal Ramdas Mahajan, Bappa Das
, Dayesh Murgaokar, Ittai Herrmann
, Katja Berger
, Rabi N. Sahoo, Kiran Patel, Ashwini Desai, Shaiesh Morajkar
, Rahul M. Kulkarni:
Monitoring the Foliar Nutrients Status of Mango Using Spectroscopy-Based Spectral Indices and PLSR-Combined Machine Learning Models. Remote. Sens. 13(4): 641 (2021)
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