Author

K. Vigneshkumar

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#explainable ai Open access Oct 2026

Deforestation & Land-Use Change: Artificial Intelligence Approaches for Detection, Attribution, and Predictive Monitoring Of Global Forest Loss

Abstract Deforestation and land-use change remain among the most consequential drivers of biodiversity loss, carbon emissions, and hydrological disruption worldwide. Traditional monitoring approaches, which rely on periodic satellite surveys and manual interpretation, are often too slow to support timely conservation i...

A Seyad Abuthahir, M Navin, K. Vigneshkumar et al. · Zenodo (CERN European Organi... · 0 citations

#federated learning Open access Oct 2026

Precision Agriculture Using AI for Crop Yield Prediction and Disease Detection: A Comprehensive Review of Machine Learning and Deep Learning Approaches for Sustainable, Data-Driven Farming

Abstract Precision agriculture amalgamates artificial intelligence (AI) with field-level sensors to enhance agricultural yield while reducing resource use. This article offers an extensive examination of the application of machine learning (ML) and deep learning (DL) methodologies to two essential functions: forecastin...

M. Ramsundhar, K Pongiri, A. R. Jayasudha et al. · Zenodo (CERN European Organi... · 0 citations

#graph neural networks Open access Oct 2026

Artificial Intelligence Applications in Climate Change Prediction

Abstract Climate change presents a growing danger to ecosystems, infrastructure, and human safety, heightening the need for prediction systems that are both precise and rapid enough to facilitate prompt decision-making. Artificial intelligence (AI), especially deep learning, has arisen as a revolutionary enhancement to...

S Suren Babu, K Sakthi, K Vinotha et al. · Zenodo (CERN European Organi... · 0 citations