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
- Josephine Theresa S, Graph Neural Network Ensemble with Particle Swarm Optimization for Privacy-Preserving Thermal Comfort Prediction , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
- S. Ranganathan, V. Umadevi, FDBSCAN-MBKSched: A Hybrid Edge-Cloud Clustering and Energy-Aware Federated Learning Framework with Adaptive Update Scheduling for Healthcare IoT , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
- A. Rukmani, C. Jayanthi, Fuzzy optimization trust aware clustering approach for the detection of malicious node in the wireless sensor networks , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Yanbo Wang, Yonghong Zhu, Jingjing Liu, Research on the current situation and influencing factors of college students learning engagement in a blended teaching environment , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Manpreet Kaur, Shweta Mishra, A smart grid data privacy-preserving aggregation approach with authentication , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- M. Kohila, S. Rethinavalli, A P2ECAM: A Trust-Preserving Cross-Cloud Data Migration Model For Resource-Constrained Mobile Devices Using Certificate-Free Elliptic Curve Cryptography , The Scientific Temper: Vol. 17 No. 02 (2026): The Scientific Temper
- Temesgen A. Asfaw, Batch size impact on enset leaf disease detection , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Deepa S, Sripriya T, Radhika M, Jeneetha J. J, Experimental evaluation of artificial intelligence assisted heart disease prediction using deep learning principle , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- B. Kalpana, P. Krishnamoorthy, S. Kanageswari, Anitha J. Albert, Machine learning approaches for predicting species interactions in dynamic ecosystems , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- A. Sathya, M. S. Mythili, MOHCOA: Multi-objective hermit crab optimization algorithm for feature selection in sentiment analysis of Covid-19 Twitter datasets , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
<< < 4 5 6 7 8 9 10 11 12 13 > >>
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
