Web-SpikeSegNet: Deep Learning Framework for Recognition and Counting of Spikes From Visual Images of Wheat Plants. - Tanuj Misra; Alka Arora; Sudeep Marwaha; Ranjeet Ranjan Jha; Mrinmoy Ray; Rajni Jain; Atmakuri Ramakrishna Rao; Eldho Varghese; Shailendra Kumar; Sudhir Kumar 003; Aditya Nigam; Rabi Narayan Sahoo; et al. (IEEE Access, 2021)

Yield-SpikeSegNet: An Extension of SpikeSegNet Deep-Learning Approach for the Yield Estimation in the Wheat Using Visual Images. - Tanuj Misra; Alka Arora; Sudeep Marwaha; Ranjeet Ranjan Jha; Mrinmoy Ray; Shailendra Kumar; Sudhir Kumar 003; Viswanathan Chinnusamy (Appl. Artif. Intell., 2022)

Inclusion of fractal dimension in four machine learning algorithms improves the prediction accuracy of mean weight diameter of soil. - Abhradip Sarkar; Pragati Pramanik Maity; Mrinmoy Ray; Debashis Chakraborty; Bappa Das; Arti Bhatia (Ecol. Informatics, 2023)

Hidden Markov guided Deep Learning models for forecasting highly volatile agricultural commodity prices. - G. Avinash; V. Ramasubramanian; Mrinmoy Ray; Ranjit Kumar Paul; Samarth Godara; G. H. Harish Nayak; Rajeev Ranjan Kumar; B. Manjunatha; Shashi Dahiya; Mir Asif Iquebal (Appl. Soft Comput., 2024)

Transformer-based deep learning architecture for time series forecasting. - G. H. Harish Nayak; Md Wasi Alam; G. Avinash; Rajeev Ranjan Kumar; Mrinmoy Ray; Samir Barman; K. N. Singh; B. Samuel Naik; Nurnabi Meherul Alam; Prasenjit Pal; Santosha Rathod; Jaiprakash Bisen (Softw. Impacts, 2024)

Improved Sieve Bootstrap based prediction intervals for time series. - Samir Barman; V. Ramasubramanian; Mrinmoy Ray (Commun. Stat. Simul. Comput., 2024)

Intelligent decision support for drought stress (IDSDS): An integrated remote sensing and artificial intelligence-based pipeline for quantifying drought stress in plants. - Arpan Kumar Maji; Sumanta Das; Sudeep Marwaha; Sudhir Kumar 003; Suman Dutta; Malini Roy Choudhury; Alka Arora; Mrinmoy Ray; Anbukkani Perumal; Viswanathan Chinusamy (Comput. Electron. Agric., 2025)

Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting. - G. H. Harish Nayak; Md Wasi Alam; B. Samuel Naik; B. S. Varshini; G. Avinash; Rajeev Ranjan Kumar; Mrinmoy Ray; K. N. Singh (J. Big Data, 2025)