Hand Gesture Identification for Improving Accuracy Using Convolutional Neural Network(CNN)
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2022.13.247Keywords:
Hand Gesture, Machine Learning, ASL Data Set, Convolutional Neural Network;Dimensions Badge
Issue
Section
License
Copyright (c) 2022 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Hand gestures are a type of non-verbal communication that uses visible body movements to convey important messages. This paper presents a much better approach of hand gesture prediction. Image Identification is an important step in most of the modern hand gesture prediction system. A convolutional neural network are used for improving the accuracy of the system. Proposed system tested for large number of hand gesture images using Tensor flow tool . The convolutional neural network (ConvNet) is a deep learning algorithm for learning and classifying hand gestures and achieved accuracy 93.61%.Abstract
How to Cite
Downloads
Similar Articles
- R. Thiagarajan, S. Prakash Kumar, Performance of public transport appraisal using machine learning , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Sindhu S, L. Arockiam, DRMF: Optimizing machine learning accuracy in IoT crop recommendation with domain rules and MissForest imputation , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- D. Jayadurga, A. Chandrabose, Distribution of virtual machines with SVM-FFDM approach in cloud computing , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Bajeesh Balakrishnan, Swetha A. Parivara, E-HRM: Learning approaches, applications and the role of artificial intelligence , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- S. Hemalatha, N. Vanjulavalli, K. Sujith, R. Surendiran, Chaotic-based optimization, based feature selection with shallow neural network technique for effective identification of intrusion detection , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- P. S. Dheepika, V. Umadevi, An optimized approach for detection and mitigation of DDoS attack cloud using an ensembled deep learning approach , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- P. J. Robinson, S. W. A. Prakash, Stochastic artificial neural network for magdm problem solving in intuitionistic fuzzy environment , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Gautam Nayak, Parthivkumar Patel, Developing speaking skills through task-based learning in English as a foreign language classroom , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Olivia C. Gold, Jayasimman Lawrence, Ensemble of CatBoost and neural networks with hybrid feature selection for enhanced heart disease prediction , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- G. Deena, K. Raja, M. Azhagiri, W.A. Breen, S. Prema, Application of support vector classifier for mango leaf disease classification , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
<< < 5 6 7 8 9 10 11 12 13 14 > >>
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- Rajesh Kumar Singh, Genetic Variability in Aromatic Rice , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper