Pratik Roy

Vellore Institute of Technology University

Papers

Total Citations

H-Index

About

Pratik Roy is a researcher at the intersection of computer vision and industrial automation, with a primary focus on deep learning-based object recognition and sorting systems. His most cited work, "Color Based Object Sorting System using Deep Learning" (2020), addresses a critical bottleneck in manufacturing: the inefficiency and inconsistency of manual object sorting. By applying convolutional neural networks to color-based classification, Roy demonstrated how deep learning can automate a traditionally menial yet quality-critical task, reducing time and human error in production lines. Though his citation count stands at 2, the practical relevance of his research—targeting real-world industrial challenges—marks him as an emerging voice in applied AI. His work contributes to the broader push for intelligent automation, where machine vision replaces repetitive human labor. For students and researchers exploring the deployment of deep learning in resource-constrained or industrial settings, Roy’s approach offers a grounded example of how to bridge algorithmic innovation with tangible, low-cost solutions. His focus on color-based sorting also opens avenues for further work in multi-spectral and real-time object classification systems.