Home Automation through Hand Gestures Using ResNet50 and 3D-CNN
Home Automation through Hand Gestures Using ResNet50 and 3D-CNN
Author(s): Ankitha Raksha, Raghul Krishna Rajasekaran, Praveen Francis, Suhas Yogeshwara, Alexander I. IlievSubject(s): Library and Information Science, Information Architecture, Library operations and management, Electronic information storage and retrieval
Published by: Институт по математика и информатика - Българска академия на науките
Keywords: Hand Gestures; Home Automation; ResNet50; 3D-CNN.
Summary/Abstract: This paper talks about using hand movements for the operations of electrical equipment at home. With the use of the much-advanced algorithms - 3D-CNN and ResNet50 to increase the accuracy in detecting the hand gesture to correctly predict the right motion for the functioning of the electrical device. Eventually, the project focuses on the comparative study between different architectures so that we can determine the best-suited model for these kinds of image detection. We aim to bring about a good accurate model for detecting the hand signals.
Journal: Digital Presentation and Preservation of Cultural and Scientific Heritage
- Issue Year: 2021
- Issue No: XI
- Page Range: 215-226
- Page Count: 12
- Language: English