Welcome to the InfoSci Platform
Reference Hub1
Object Detection Using Region-Conventional Neural Network (RCNN) and OpenCV

Object Detection Using Region-Conventional Neural Network (RCNN) and OpenCV

Kande Archana, Kamakshi Prasad
Copyright: © 2022 |Volume: 14 |Issue: 2 |Pages: 9
ISSN: 2637-7888|EISSN: 2637-7896|EISBN13: 9781683183488|DOI: 10.4018/IJDAI.315277
Cite Article Cite Article

MLA

Archana, Kande, and Kamakshi Prasad. "Object Detection Using Region-Conventional Neural Network (RCNN) and OpenCV." IJDAI vol.14, no.2 2022: pp.1-9. http://doi.org/10.4018/IJDAI.315277

APA

Archana, K. & Prasad, K. (2022). Object Detection Using Region-Conventional Neural Network (RCNN) and OpenCV. International Journal of Distributed Artificial Intelligence (IJDAI), 14(2), 1-9. http://doi.org/10.4018/IJDAI.315277

Chicago

Archana, Kande, and Kamakshi Prasad. "Object Detection Using Region-Conventional Neural Network (RCNN) and OpenCV," International Journal of Distributed Artificial Intelligence (IJDAI) 14, no.2: 1-9. http://doi.org/10.4018/IJDAI.315277

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Object detection is used in almost every real-world application such as autonomous traversal, visual system, face detection, and even more. This paper aims at applying object detection technique to assist visually impaired people. It helps visually impaired people to know about the objects around them to enable them to walk free. A prototype has been implemented on a Raspberry PI3 using OpenCV libraries, and satisfactory performance is achieved. In this paper, a detailed review has been carried out on object detection using region-conventional neural network (RCNN)-based learning systems for a real-world application. This paper explores the various process of detecting objects using various object detections methods and walks through detection including a deep neural network for SSD implemented using Caffee model.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.