Sign Language Classifier based on Machine Learning - Avram, Camelia; Păcurar, Laura – Flavia; Radu, Dan (Technologia i Automatyzacja Montażu (Assembly Techniques and Technologies), 2024)
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.