… the process of feature extraction from meta data by processing it through a number of … deep learning architecture usingconvolutionalneuralnetwork to recognize the static handgestures…
… handgesturerecognition is presented. The study includes the recognition of handgestures based on RGB cameras and depth sensors using machine learning and deeplearning …
S Sharma, S Singh - Expert Systems with Applications, 2021 - Elsevier
… The handgestures are the foundation of sign language… deeplearning based convolutional neuralnetwork (CNN) model is specifically designed for the recognition of gesture-based sign …
… to other deeplearning models. By using YOLOv3, our handgesturerecognition system has … Furthermore, we will design a more advanced convolutionneuralnetwork with data fusion, …
… convolutionalneuralnetwork (CNN) was implemented to decode handgesturesfrom the sEMG data recorded from … With advancements in deeplearning, many studies have explored …
YS Tan, KM Lim, CP Lee - Expert Systems with Applications, 2021 - Elsevier
… Convolutionalneuralnetwork (CNN) is one of the method fromdeeplearning approach, it is predominantly applied in imagerecognition tasks, including sign language …
DS Tran, NH Ho, HJ Yang, ET Baek, SH Kim, G Lee - Applied Sciences, 2020 - mdpi.com
… This paper presented a new approach to handgesturerecognitionusing a combination of geometry algorithm and a deeplearning method to achieve fingertip detection and …
W Zhang, J Wang, F Lan - IEEE/CAA Journal of Automatica …, 2020 - ieeexplore.ieee.org
… Vision based dynamic handgesturerecognition has become a hot research topic due to its … a novel deeplearningnetwork for handgesturerecognition. The network integrates several …
B Hu, J Wang - International Journal of Automation and Computing, 2020 - Springer
… software system based on deeplearningneuralnetworks. It is our … in deeplearningnetwork based handgesturerecognition. The … of deeplearning. Section 3 gives an overview of the …