Karthik, Pillarisetty Uday and Vurakaranam, Sai Subbarao and M, Sumalatha and R, Renugadevi and Anitha, Sunkara (2025) Developing an Efficient and Lightweight Deep Learning Model for an American Sign Language Alphabet Recognition Applying Depth Wise Convolutions and Feature Refinement. In: Proceedings of the 4th International Conference on Information Technology, Civil Innovation, Science, and Management, ICITSM 2025, 28-29 April 2025, Tiruchengode, Tamil Nadu, India, Part I.
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Abstract
In this, we proposed a deep learning framework for classifying American Sign Language (ASL) alphabet gestures to support accessibility for people with speech and hearing impairment. We evaluated our model using three public ASL datasets. one of the datasets of 87,000+ real-time images and 29 classes
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Date Deposited: | 04 Mar 2026 20:17 |
| Last Modified: | 16 Apr 2026 15:59 |
| URI: | http://eprints.eai.eu/id/eprint/60055 |
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