Papers
1
Total Citations
2
H-Index
1
About
Kumar Rahul is a researcher at the forefront of applying computer vision technologies to food quality and safety assurance. His work bridges advanced image processing and machine learning to address critical challenges in the food industry, particularly in automating inspection and ensuring product integrity. His most-cited paper, "Computer Vision Technologies for Food Quality and Safety Assurance: Evaluating Trends and Analytical Results" (2026), has garnered 2 citations, reflecting a growing interest in his systematic evaluation of emerging trends and analytical methodologies. Rahul’s contributions lie in synthesizing diverse vision-based approaches—from hyperspectral imaging to deep learning classifiers—to enhance detection of contaminants, spoilage, and grading inconsistencies. By critically assessing the strengths and limitations of current technologies, he provides a roadmap for future innovations in non-destructive testing and real-time monitoring. His work is particularly valuable for researchers and practitioners seeking to integrate reliable, cost-effective computer vision systems into food supply chains. Rahul’s research not only advances academic understanding but also holds practical implications for improving global food safety standards, making him a notable voice in this interdisciplinary field.
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Top Papers
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