Detection of Vehicular Traffic Using Convolutional Neural Networks
Sai Krishna. Parachoori1, K. Sujatha2, M. Anand3, T. Godhavari4, S. Jayalakshmi5
1Sai Krishna. Parachoori, Research Scholar, ECE Dept., Dr. MGR Educational & Research Institute, Chennai, Tamil Nadu, India.
2Dr. K. Sujatha, Professor, EEE Dept., Dr. MGR Educational & Research Institute, Chennai, Tamil Nadu, India.
3Dr. M. Anand, Professor, ECE Dept., Dr. MGR Educational & Research Institute, Chennai, Tamil Nadu, India.
4Dr. T. Godhavari, Professor, ECE Dept., Dr. MGR Educational & Research Institute, Chennai, Tamil Nadu, India.
5S. Jayalakshmi, Professor, Department of EEE, Ramachandra College of Engineering, Eluru, Andhra Pradesh, India.
Manuscript received on 05 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 August 2019 | PP: 1423-1426 | Volume-8 Issue-10, August 2019 | Retrieval Number: J10080881019/19©BEIESP | DOI: 10.35940/ijitee.A1008.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In present generation the detection of vehicle using aerial images plays an important role and mot challenging. The video understanding, border security are the applications of aerial images. To improve the performance of the system different detection methods are introduced. But these methods take more time in detection process. To overcome these convolutional neural network are introduced which will produce the successful design system. the main intent of this paper is to present the recognition system for aerial images using convolutional neural network. The proposed method improves the accuracy and speed after the detection process. At last aerial image is obtained by matching the image and textual description of classes.
Keywords: Vehicle detection; convolutional neural network; aerial image.
Scope of the Article: Neural Network