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
- Manisha Anil Vhora, Vidya Bhandwalkar, Prashant Mangesh Rege, AI-driven HR analytics: Enhancing decision-making in workforce planning , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- R. Selvakumar, A. Manimaran, Janani G, K.R. Shanthy, Design and development of artificial intelligence assisted railway gate controlling system using internet of things , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Samara Ahmed, Adil E. Rajput, Denial, acceptance and intervention in society regarding female workplace bullying - A mental health study on social media , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Subin M. Varghese, K. Aravinthan, A robust finger detection based sign language recognition using pattern recognition techniques , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Rupesh Mandal, Bobby Sharma, Dibyajyoti Chutia , Smart flood monitoring in Guwahati city: A LoRa-based AIoT and edge computing sensor framework , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Akanksha Singh, Nand Kumar, Analysis of renewable energy and economic growth of Germany , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Krishna P. Kalyanathaya, Krishna Prasad K, A novel method for developing explainable machine learning framework using feature neutralization technique , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- S. Bhuvaneswari, A. Nisha Jebaseeli, Multi-model telecom churn prediction , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- S. Sindhu, L. Arockiam, A lightweight selective stacking framework for IoT crop recommendation , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Nitin J. Wange, Sachin V. Chaudhari, Koteswararao Seelam, S. Koteswari, T. Ravichandran, Balamurugan Manivannan, Algorithmic material selection for wearable medical devices a genetic algorithm-based framework with multiscale modeling , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
<< < 11 12 13 14 15 16 17 18 19 20 > >>
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
