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
- Ayalew Ali, Sitotaw Wodajo, Taye Teshoma, The link between corporate governance and earnings management of insurance companies in Ethiopia , The Scientific Temper: Vol. 16 No. 07 (2025): The Scientific Temper
- Geetha Satish Pisharody, Sanjay Gupta, Understanding Resilience: An Analytical Study of Adversity Quotient Levels Among Higher Secondary Learners in Gujarat State , The Scientific Temper: Vol. 17 No. 01 (2026): The Scientific Temper
- Hashmat Ali, Nishant Soren, Rohit Kumar Ravi, Kunal Kumar, Anjali, Evaluation of Standard Changes in Enthalpy During Complex Formation of Mn(II), Ni(II), Cd(II) and Hg(II) with p-fluorobenzoylthioacetophenone , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper
- Suresha S, Corporate bonds vis-a-vis bond market: Global economy , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Aditi Malik, Rishi Chaudhry, Mohit, Urvashi Suryavanshi, Mapping the landscape of political advertising research: A comprehensive bibliometric analysis , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- A. Kalaiselvi, A. Chandrabose, Fuzzy logic-driven scheduling for cloud computing operations: a dynamic and adaptive approach , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Amanda Quist Okronipa, Lucy Ewuresi Eghan, A theoretical investigation of students’ adoption of artificial intelligence chatbots using social cognitive theory and uses and gratification theory , The Scientific Temper: Vol. 16 No. 02 (2025): The Scientific Temper
- Sirajum Munira Priety, Farhan Bin Manjur, AI Driven Approach in Smart Manufacturing in Bangladesh , The Scientific Temper: Vol. 16 No. 10 (2025): The Scientific Temper
- Jasmine A, G. Arul Selvi, Exploring Behavioural Dimensions of Social Media Engagement: An Exploratory Factor Analysis Among College Youth , The Scientific Temper: Vol. 17 No. 02 (2026): The Scientific Temper
- AMRINAL CHANDRA, H.C. RAI, “SYNTHESIS AND SPECTRAL STUDIES OF Co(II) AND Ni(II) COMPLEXES WITH SCHIFF BASE LIGAND 1,6-DIMERCAPTO-1,6 DIAMINO-2,4,5-TRIAZA-3-PHENYL-3-HEXENE” , The Scientific Temper: Vol. 8 No. 1&2 (2017): The Scientific Temper
<< < 44 45 46 47 48 49 50 51 52 53 > >>
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

