HAND GESTURE RECOGNITION USING AI/ML

Authors

  • Tejasvi Jawalkar Department of Computer Engineering, JSPM’s Imperial College of Engineering and Research, Wagholi, Pune
  • Sejal Khalate Department of Computer Engineering, JSPM’s Imperial College of Engineering and Research, Wagholi, Pune
  • Shweta Medhe Department of Computer Engineering, JSPM’s Imperial College of Engineering and Research, Wagholi, Pune
  • Kshitija Palaskar Department of Computer Engineering, JSPM’s Imperial College of Engineering and Research, Wagholi, Pune

Keywords:

Human-computer interaction, hand gesture detection, artificial intelligence, machine learning, convolutional and recurrent neural networks

Abstract

An essential component of human-computer interaction is hand gesture recognition, which enables natural and instinctive verbal communication between users and computers. This paper offers a thorough assessment of recent developments in the field of hand gesture identification through the use of system research (ML) and artificial intelligence (AI) techniques. We discuss the difficult scenarios, approaches, and packages related to reputation structures for hand gestures. The effectiveness of various AI and ML techniques, including deep learning models like recurrent neural networks (RNNs) and convolutional neural networks (CNNs), in identifying hand motions from camera or sensor data is investigated. Since sign language is made up of continuous movements, in order for it to become popular, it must capture motion facts across a few successive frames from a video. This study describes two-way communication between the deaf, the dumb, and normal people. As a result, the suggested gadget can translate sign language into text and voice.

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Published

2024-05-20

How to Cite

[1]
Tejasvi Jawalkar, Sejal Khalate, Shweta Medhe, and Kshitija Palaskar, “HAND GESTURE RECOGNITION USING AI/ML”, IEJRD - International Multidisciplinary Journal, vol. 9, no. 2, p. 8, May 2024.

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