Virtual keyboard using machine learning

This research introduces an innovative virtual keyboard system leveraging machine vision for human-computer interaction. The system utilizes hand tracking and recognition to facilitate virtual keyboard control without physical touch. This paper details the system architecture, implementation, and experimental results. This research introduces a novel approach to virtual keyboards using machine vision, providing an innovative and cost-effective solution for human-computer interaction. The system employs hand tracking and recognition to enable users to control a virtual keyboard without physical touch. The headway of innovation has prompted registering being coordinated into cell phones like cell phones and palm tops. Be that as it may, the conventional QWERTY console stays unaltered as the essential info gadget. This paper proposes a virtual console application that uses picture handling to make a visual ortrayal of a console. The virtual console will be useful and open by utilizing a camera to catch hand motions as composing inputs. A similar idea applies to the improvement of a virtual mouse that will involve finger acknowledgment as data sources. The camera will catch hand developments to control the mouse. The virtual console and mouse will be made by getting the picture of a console or mouse utilizing the camera, and catching the composing or mouse developments.