Research ArticleOpen accessPhrase in the titleOptimization of Multi-Layer Perceptron Deep Neural Networks using Genetic Algorithms for Hand Gesture RecognitionKhanh Nguyen-Trong, Thi-Thanh-Tan NguyenApplications of wearable sensors for Hand Gesture Recognition (HGR) have been gaining popularity in recent years. Among the proposed methods, deep neural networks with many hidden layers are promising to address the requirements of this wearable activity recognition. They can directly uncover features tied to the dynamics of HGR, from simple motion encoding in lower layers to more complex motion … …Journal of Computer Science, Vol. 18, Issue 2 · 8 Feb 2022 · 7,180 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleHand Gesture Recognition for Human-Computer InteractionS. Mohamed Mansoor Roomi, R. Jyothi Priya, H. JayalakshmiProblem statement: With the development of ubiquitous computing, current user interaction approaches with keyboard, mouse and pen are not sufficient. Due to the limitation of these devices the useable command set is also limited. Direct use of hands can be used as an input device for providing natural interaction. Approach: In this study, Gaussian Mixture Model (GMM) was used to … …Journal of Computer Science, Vol. 6, Issue 9 · 30 Sep 2010 · 8,311 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRemoAct: Portable Projected Interface with Hand Gesture InteractionHussam Saad Adeen, Ayman Atia, Ahmad Amin et al.RemoAct is a wearable depth sensing and projection system that enables interaction on many surfaces. It makes interaction with the environment more intuitive through sharing and sending data with surrounding devices by applying certain gestures. This system offers a mobile and intuitive solution for interacting using a projected surface on habitual flat surfaces. Every user has their public and private … …Journal of Computer Science, Vol. 11, Issue 5 · 4 Aug 2015 · 8,146 accessesView PDFCite
Research ArticleOpen accessIn the abstractStatic Hand Gestures: Fingertips Detection Based on Segmented ImagesAhmad Yahya Dawod, Md Jan Nordin, Junaidi AbdullahFingertips detection is important for recognition of static gesture in sign language. This paper presents a new method that is based on YCbCr colour space and skeletonization for fingertips detection towards gesture segmentation and recognition. The method begins with the conversion of an image in RGB colour space into YCbCr colour space. Then, the chrominance Cb and Cr are extracted … …Journal of Computer Science, Vol. 11, Issue 12 · 4 Feb 2016 · 7,032 accessesView PDFCite
Research ArticleOpen accessIn the abstractA REVIEW ON THE DEVELOPMENT OF INDONESIAN SIGN LANGUAGE RECOGNITION SYSTEMSutarman, Mazlina Abdul Majid, Jasni Mohamad ZainSign language is mainly employed by hearing-impaired people to communicate with each other. However, communication with normal people is a major handicap for them since normal people do not understand their sign language. Sign language recognition is needed for realizing a human oriented interactive system that can perform an interaction like normal communication. Sign language recognition basically uses two approaches: … …Journal of Computer Science, Vol. 9, Issue 11 · 27 Sep 2013 · 8,691 accessesView PDFCite
Research ArticleOpen accessIn the abstractSkin Color Detection Model Using Neural Networks and its Performance EvaluationK. K. Bhoyar, O. G. KakdeProblem statement: Skin color detection is used as a preliminary step in numerous computer vision applications like face detection, nudity recognition, hand gesture detection and person identification. In this study we present a pixel based skin color classification approach, for detecting skin pixels and non skin pixels in color images, using a novel neural network symmetric classifier. The neural classifiers … …Journal of Computer Science, Vol. 6, Issue 9 · 30 Sep 2010 · 8,058 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordRecognizing Sign Language Gestures Using a Hybrid Spatio-Temporal Deep Learning ModelMeryem Cherrate, My Abdelouahed Sabri, Ali Yahyaouy, Abdellah AarabRecognizing gestures in American Sign Language (ASL) from video data presents significant challenges due to the intricate combination of hand gestures, facial cues, and body motion. In this work, we introduce a hybrid deep learning framework that integrates Convolutional Neural Networks (CNNs) for extracting spatial characteristics with Long Short-Term Memory (LSTM) networks for capturing temporal sequences. The model was trained … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,048 accessesView PDFCite