Chandan Kumar Singh

Papers

Total Citations

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About

Chandan Kumar Singh is a researcher at the forefront of computer vision and deep learning, with a particular focus on automating industrial and warehouse processes. His most cited work, "Deep Network based Automatic Annotation for Warehouse Automation" (2018), tackles a critical bottleneck in applied AI: the immense manual labor required to generate training datasets. By proposing a fully automatic object annotation technique, Singh’s research directly addresses the scalability challenges of deploying deep networks in real-world environments. This contribution has garnered 4 citations, signaling its relevance to the growing field of automated data generation. Singh’s work is notable for bridging the gap between theoretical deep learning advances and practical industrial applications, offering solutions that reduce human effort while maintaining annotation accuracy. For students and researchers exploring efficient dataset creation or warehouse automation, Singh’s research provides a foundational approach to leveraging deep networks for self-supervised or semi-automated learning pipelines. His focus on reducing manual intervention in AI training processes positions him as a key contributor to the next generation of autonomous systems.