OBJECT RECOGNITION FROM VIDEO SEQUENCES IN REAL TIME USING DEEP LEARNING TECHNIQUES

Authors

Keywords:

Objects Recognition, Deep Learning, Computer Vision

Abstract

In the field of computer vision, a wide range of applications has been developed for various purposes. Object recognition in images has always been a relevant task in this application domain. Nowadays, new methods have been developed to achieve greater accuracy and efficiency in the process of object detection. In this research, a comparative analysis of the main methods based on deep learning was carried out, which are among the most effective for object detection and classification.  It was proposed an implementation based on the YOLO algorithm for object recognition in video sequences, which uses the library for computer vision OpenCV. Experiments designed to validate the proposed solution were performed on two different computation nodes and the results obtained were analyzed according to the main metrics employed to evaluate the performance of object recognition methods.

Downloads

Download data is not yet available.

Downloads

Published

2021-01-30

How to Cite

García Cotrina, E., Hernández Duany, O. A., & García Albert, A. (2021). OBJECT RECOGNITION FROM VIDEO SEQUENCES IN REAL TIME USING DEEP LEARNING TECHNIQUES. Telemática, 20(2). Retrieved from https://revistatelematica.cujae.edu.cu/index.php/tele/article/view/459

Most read articles by the same author(s)