Abstract
The progress in the realm of machine learning has caused the field of image processing to undergo a significant advancement. Image processing is a vast subject due to the diverse algorithms and techniques that can be implemented. Sign Language is the hearing disabled community’s way of conveying information and this dissertation was drafted to understand and provide them with what little assistance we can. Visual cues and signs are used to convey messages and intentions of the speaker. It is a well-developed language that has its own vocabulary and grammar. In this paper, we analyze the various methods used in converting Sign Language into text which can be read or to audio that can be heard. This treatise also includes our very own methodology, which makes use of a CNN architecture called AlexNet and discusses the results of the same.
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Saravanan, R., Retnaswamy, S., Selvan, S. (2022). A Method of Hand Gestures Recognition using Convolutional Neural Network. In: Sivasubramanian, A., Shastry, P.N., Hong, P.C. (eds) Futuristic Communication and Network Technologies. VICFCNT 2020. Lecture Notes in Electrical Engineering, vol 792. Springer, Singapore. https://doi.org/10.1007/978-981-16-4625-6_34
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DOI: https://doi.org/10.1007/978-981-16-4625-6_34
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