Indian Sign Language Recognition Using CNN Inception V3 - A Review

Abstract

This research paper explores the intersection of sign language recognition & deep learning, with a focus on the utilization of CNNs and the Inception V3 architecture. The study emphasizes how crucial proper translation and identification of sign language is to closing the communication gap that exists between the hearing and the Deaf populations. It discusses challenges such as limited datasets and ambiguity in sign language and outlines the potential for future advancements in accessibility and education. By combining the power of deep learning and culturally tailored datasets, this research paper paves the way for more effective sign language recognition, offering the promise of improved communication and accessibility for individuals with hearing impairments. It emphasizes how important it is to remove obstacles to communication and promote inclusion in all facets of daily life for the community of people who are Deaf and hard of hearing