22 citations · 41 across the 7 of their papers we have counts for
7 papers
Claims, Designs, and Guarantees: A Critical Narrative Review of Statistical Inference Reform and Practice, 2016--2026
Aswini Kumar Patra, Shashi Bhushan Jha
Statistics helps scientists decide what their data show, but its most familiar tool, the -value, is widely misunderstood. Between 2016 and 2026, professional bodies issued new g…
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…
Improved Classification of Nitrogen Stress Severity in Plants Under Combined Stress Conditions Using Spatio-Temporal Deep Learning Framework
Aswini Kumar Patra, Anshu Rastogi, Lingaraj Sahoo
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-…
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…
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…
Explainable Light-Weight Deep Learning Pipeline for Improved Drought Stress Identification
Aswini Kumar Patra, Lingaraj Sahoo
Early identification of drought stress in crops is vital for implementing effective mitigation measures and reducing yield loss. Non-invasive imaging techniques hold immense potent…