Hand Gesture Recognition By Deep Convolutional Neural Network - et. al., T.Kumaravel , (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Today the hand gesture is increasingly in the human-computer interactions. In all project, there is a minimum number of the process involved in the hands only and maximum contains the body, background, etc., In this paper, it shows that the location of the hand, hand gesture, and applies it in home and also the interaction between the system and the users. Hand gesture means that it is the form of sign language in the form of passing the signals and expressions. The movement occurred in the hand is called the hand gesture which can be used in hearing loss peoples. The processing of the hand gesture is that it shares the communication to others with the help of hands. The different symbols and numbers are forming with the hands and the signs form a group of words that can be understood by other people. There are two types of hand gestures like a glove based and vision-based.In this paper, a new approach called deep convolutional neural networks, which used in hand gestures to classify the images held in the hand gesture. The deep convolutional hand gesture can be used to find a more number of hand gestures. The hand gestures require more time for processing. The convolutional neural network can be used for saving the timing and reducing the time used in the separation of things or images. Finding the state of hand gesture, which will also, needs more time. The deep CNN provides a faster process in that. Using the deep CNN method, provide the system with more accuracy, specificity, sensitivity compared to the other systems. The proposed method as CNN, which separates the different sections, provides good accuracy, specificity, sensitivity from the dataset. The system process ends until the hand gesture image is leaving from the camera.