Papers
1
Total Citations
9
H-Index
1
About
Arnab Dey is a researcher at the forefront of computer vision and human-computer interaction, with a specialized focus on sign language recognition and gesture-based communication systems. His work addresses the critical challenge of bridging communication gaps for individuals with hearing impairments through deep learning and video analysis. Dey’s most notable contribution, "Recognition of Wh-Question Sign Gestures in Video Streams using an Attention Driven C3D-BiLSTM Network" (2024), introduces an innovative hybrid architecture that combines 3D convolutional neural networks with bidirectional long short-term memory networks, enhanced by attention mechanisms. This approach achieves robust recognition of question-specific sign gestures in continuous video streams, a significant step toward real-time, natural sign language interpretation. With 9 citations already, this work is gaining traction for its practical applicability in assistive technologies. Dey’s research not only advances the technical frontiers of spatiotemporal gesture analysis but also underscores a deep commitment to inclusive technology, aiming to empower non-verbal individuals and facilitate seamless interaction between hearing and deaf communities.
Research Focus
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Top Papers
- 1