Papers

4

Total Citations

117

H-Index

3

About

Anichur Rahman is a researcher working at the intersection of computer vision, deep learning, and intelligent systems, with a particular focus on human-centered computing and IoT-integrated robotics. His most recognized contribution is a novel four-layer Convolutional Neural Network (ConvNet) architecture designed for facial emotion recognition, which has garnered over 100 citations since its publication — a testament to its significance within the field. This work addresses a critical challenge in affective computing by achieving reliable emotion classification with minimal training epochs while emphasizing the vital role of data diversity in model generalization. The practical implications of this research span numerous domains, including human-computer interaction, medical diagnostics, data-driven animation, and human-robot communication, making it broadly relevant across both academic and applied settings. Beyond emotion recognition, Rahman has extended his expertise into autonomous robotics, contributing to the development of an IoT-integrated fire extinguishing and surveillance robot that demonstrates the growing convergence of smart sensing and robotic systems. Collectively, his work reflects a consistent commitment to building intelligent, real-world solutions through innovative applications of machine learning and connected technologies.

Research Focus

Key Achievements

3
H-Index
4
Papers
117
Total Citations
29
Avg Citations/Paper
🏆 Most Cited Paper
Four-layer ConvNet to facial emotion recognition with minimal epochs and the significance of data diversity
100 citations · 2022
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: University of Dhaka, Mawlana Bhashani Science and Technology University, Bangladesh University of Textiles

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago