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
- Tara K. Sharma, Problems and prospects of tourism financing in Sikkim , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Iftikhar A. Tayubi, Mayur D. Jakhete, Spoorthi B. Shetty, Ashish Verma, Mohit Tiwari, S. Kiruba, Sustainable healthcare AI-enhanced materials discovery and design for eco-friendly and biocompatible medical applications , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- L Brigith Gladys, J Merline Vinotha, Multi-objective Multi-route Soft Rough Sustainable Transportation Problem based on Various Road Maintenance Conditions , The Scientific Temper: Vol. 16 No. 10 (2025): The Scientific Temper
- Jayendra K. Singh, Gyan P. Singh, Sanjay K. Singh, Son preference and children sex composition in Uttar Pradesh: An empirical analysis , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Neha Verma, Beyond likes & clicks: Empowering role of social media marketing in value creation , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Hannah Ayaba Tanye, Henry Akwetey Matey, Isaac Asampana, Albert Akanlisikum Akanferi, Douglas Yeboah , Augustina Dede Agor, Assessing the information security awareness among Ghanaian University students , The Scientific Temper: Vol. 16 No. 07 (2025): The Scientific Temper
- Shriram N. Kargaonkar, Sushma Pradeep Chalke, Sunil Mahajan, Statistical Modeling of Consumer Preferences for Eco-friendly Digital Products: A Data-driven Approach Toward Sustainable Consumption in India , The Scientific Temper: Vol. 16 No. 10 (2025): The Scientific Temper
- B. Nivedetha, Water Quality Prediction using AI and ML Algorithms , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- Rekha R., P. Meenakshi Sundaram, Trust aware clustering approach for the detection of malicious nodes in the WSN , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Merla Agnes Mary, Britto Ramesh Kumar, Hybrid GAN with KNN - SMOTE Approach for Class-Imbalance in Non-Invasive Fetal ECG Monitoring , The Scientific Temper: Vol. 16 No. 09 (2025): The Scientific Temper
<< < 27 28 29 30 31 32 33 34 35 36 > >>
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

