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@article{156612,
        author = {Devivara Prasad G and Srinivasulu M},
        title = {HAND GESTURE PRESENTATION BY USING MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {4},
        pages = {253-257},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=156612},
        abstract = {Human-Computer Interaction (HCI) encompasses a wide range of interactions, including gestures. HCI gesture recognition is concerned with nonverbal communication gestures. A system may recognize human gestures and convey data to enable the operation of a gadget. This is a significant HCI subfield that deals with user and device interfaces. The purpose of gesture recognition is to capture certain gestures that can then be recognized by a device like a camera. In a number of scenarios, hand gestures can be used to communicate [1]. Deaf or hard of hearing people, as well as stroke patients, may utilize it to communicate and satisfy their fundamental requirements.
Several earlier research on hand gestures have been conducted. Several papers presented various approaches to administering hand gesture testing. There are several picture feature extraction tools available, as well as AI, which includes a number of classifiers for categorizing various sorts of data. To extract pictures and recognize distinct tiny movements and motions in 2D and 3D hand gestures, an effective approach is required [2].},
        keywords = {Hand Gesture Recognition, Human Computer Interaction, Processing of Images.},
        month = {},
        }