RSIS Repository Open-access research from RSIS International journals

International Journal of Research and Innovation in Applied Science (IJRIAS)

Indian Sign Language Alphabet Recognition Using Transfer Learning with MobileNetV2

byShalaka Gaikwad; Dr. Girish Katkar; Dr. Ajay Ramteke

Published February 25, 2026  •  Vol. 11, Issue 2, pp. 94–101Open Access
DOI: 10.51584/IJRIAS.2026.11020009

Abstract

Indian Sign Language (ISL) recognition plays a vital role in bridging the communication gap between the hearing-impaired community and the general population. This research presents an efficient deep learning-based approach for static ISL alphabet recognition using transfer learning with MobileNetV2. A dataset consisting of 26,000 images representing 26 alphabet classes (A–Z) was used. The proposed model leverages a pre-trained MobileNetV2 backbone for feature extraction, followed by custom classification layers. Experimental results demonstrate a high validation accuracy of 99% and test accuracy 99.89%, indicating the effectiveness of the approach for real-world ISL recognition tasks.

Keywords: Indian Sign Language, Transfer Learning, MobileNetV2, Deep Learning, Image Classification, Gesture Recognition

JournalInternational Journal of Research and Innovation in Applied Science (IJRIAS)
ISSN2454-6194
Volume / IssueVolume 11, Issue 2
Pages94–101
Publication dateFebruary 25, 2026
DOI10.51584/IJRIAS.2026.11020009
PublisherRSIS International
LicenseOpen Access

How to cite this article

Shalaka Gaikwad, Dr. Girish Katkar, & Dr. Ajay Ramteke (2026). Indian Sign Language Alphabet Recognition Using Transfer Learning with MobileNetV2. International Journal of Research and Innovation in Applied Science (IJRIAS), 11(2), 94-101. https://doi.org/10.51584/IJRIAS.2026.11020009

BibTeX

@article{Shalaka2026,
  title   = {Indian Sign Language Alphabet Recognition Using Transfer Learning with MobileNetV2},
  author  = {Shalaka Gaikwad and Dr. Girish Katkar and Dr. Ajay Ramteke},
  journal = {International Journal of Research and Innovation in Applied Science (IJRIAS)},
  volume  = {11},
  number  = {2},
  pages   = {94--101},
  year    = {2026},
  doi     = {10.51584/IJRIAS.2026.11020009},
  publisher = {RSIS International}
}