Sign Language Classifier based on Machine Learning
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Keywords

sign language classifier
machine learning
mobile application
sign language in assembly process

How to Cite

Avram, C., Păcurar, L. – F., & Radu, D. (2024). Sign Language Classifier based on Machine Learning. Technologia I Automatyzacja Montażu (Assembly Techniques and Technologies), 123(1), 10-15. https://doi.org/10.7862/tiam.2024.1.2

Abstract

Sign language represents an efficient way for individuals with hearing impairments to communicate. We propose a sign recognition system into which several tools are integrated to help with the image pre-processing part. By doing so, a machine learning model was developed that does not require a lot of processing power because instead of using the images themselves, it uses extracted data from them to connect this model to a mobile interface that the users will use to recognise signed letters successfully. The communication between the client and the model is sustained through a local server. Introducing sign language into assembly processes is not only a gesture of respect for diversity and inclusion but also a strategic decision that brings tangible benefits. It improves communication, safety, employee morale and overall efficiency, an essential element in achieving operational excellence and an integrated workplace.

https://doi.org/10.7862/tiam.2024.1.2
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