K.P. Ragunath

Deep Learning-Based Multi-Class Pest and Disease Detection in Agricultural Fields

Sellaperumal Pazhanivelan, K.P. Ragunath, N.S. Sudarmanian, S. Satheesh & P. Shanmugapriya · Journal of Scientific Research and Reports · 2025

Farmers and agricultural workers would manually inspect crops for signs of pests or use traps to monitor pest populations. The advent of deep learning algorithms such as vision transformers and FastAI ResNet has brought about a significant transformation in pest detection practic...

Open access Research Article 10.9734/jsrr/2025/v31i12797

Using Sentinel 1A (SAR) and Sentinel 2 Data for Assessing Water Spread Dynamics and Crop Diversification in Lower Palar Sub Basin, Tamil Nadu, India

Sellaperumal Pazhanivelan, M. Vairavamani, K.P. Ragunath, R. Kumaraperumal, N. S. Sudarmanian, S. Manikandan & S. Satheesh · International Journal of Environment and Climate Change · 2025

Sentinel-1A Synthetic Aperture Radar (SAR) satellite is highly beneficial for continuously monitoring the evaluating changes in agricultural areas and water spread area assessment. Having reliable information about water availability is crucial for effective regional planning. By...

Open access Research Article 10.9734/ijecc/2025/v15i24735

Innovative Approaches to Bengal gram Yield Mapping: Integration of Sentinel-1 SAR and Crop Simulation Models for Precision Agriculture

Sellaperumal Pazhanivelan, N.S. Sudarmanian, S. Satheesh & K.P. Ragunath · Journal of Scientific Research and Reports · 2025

Accurate spatial yield estimation is crucial for optimizing agricultural management and ensuring food security. This study integrates Sentinel-1A SAR remote sensing data and the DSSAT crop simulation model to predict Bengal gram (chickpea) yield in Nagaur district, Rajasthan, Ind...

Open access Research Article 10.9734/jsrr/2025/v31i12788