6 papers
Making Effective Statistical Inferences: From Significance Testing to the Open Science Inference Ecosystem (2016-2026)
Aswini Kumar Patra
Statistical inference has undergone a profound transformation over the past decade, evolving from a significance-testing paradigm toward a comprehensive, transparency-driven framew…
An explainable vision transformer with transfer learning based efficient drought stress identification
Aswini Kumar Patra, Ankit Varshney, Lingaraj Sahoo
Early detection of drought stress is critical for taking timely measures for reducing crop loss before the drought impact becomes irreversible. The subtle phenotypical and physiolo…
Improved Classification of Nitrogen Stress Severity in Plants Under Combined Stress Conditions Using Spatio-Temporal Deep Learning Framework
Aswini Kumar Patra, Lingaraj Sahoo, Anshu Rastogi
Plants in their natural habitats endure an array of interacting stresses, both biotic and abiotic, that rarely occur in isolation. Nutrient stress-particularly nitrogen deficiency-…
MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification
Aswini Kumar Patra, Lingaraj Sahoo
Drought stress is a major threat to global crop productivity, making its early and precise detection essential for sustainable agricultural management. Traditional approaches, thou…
MRI Patterns of the Hippocampus and Amygdala for Predicting Stages of Alzheimer's Progression: A Minimal Feature Machine Learning Framework
Aswini Kumar Patra, Soraisham Elizabeth Devi, Tejashwini Gajurel
Alzheimer's disease (AD) progresses through distinct stages, from early mild cognitive impairment (EMCI) to late mild cognitive impairment (LMCI) and eventually to AD. Accurate ide…
Improved Cotton Leaf Disease Classification Using Parameter-Efficient Deep Learning Framework
Aswini Kumar Patra, Tejashwini Gajurel
Cotton crops, often called "white gold," face significant production challenges, primarily due to various leaf-affecting diseases. As a major global source of fiber, timely and acc…