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Stefan cel Mare
University of Suceava
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ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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FEATURED ARTICLE

Analysis of the Hybrid PSO-InC MPPT for Different Partial Shading Conditions, LEOPOLDINO, A. L. M., FREITAS, C. M., MONTEIRO, L. F. C.
Issue 2/2022

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  2/2023 - 11

Robust Human Detection Using Histogram Oriented Gradient and Aggregate Channel Features

SONMEZOCAK, T. See more information about SONMEZOCAK, T. on SCOPUS See more information about SONMEZOCAK, T. on IEEExplore See more information about SONMEZOCAK, T. on Web of Science
 
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Download PDF pdficon (5,632 KB) | Citation | Downloads: 704 | Views: 714

Author keywords
gradient methods, image processing, machine learning algorithms, object detection, unmanned aerial vehicles

References keywords
detection(16), vision(9), tracking(8), pedestrian(8), object(8), visual(6), robust(6), pattern(6), features(6), applications(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2023-05-31
Volume 23, Issue 2, Year 2023, On page(s): 93 - 100
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2023.02011
Web of Science Accession Number: 001009953400011
SCOPUS ID: 85164326974

Abstract
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Today, with the development of camera imaging techniques, object detection studies are becoming popular for unmanned aerial vehicles and autonomous systems. However, in these systems, it is extremely important to be able to identify objects effectively and with minimum error in detection for tracking. In this study, an effective human detection system is proposed based on the use of support vector machine, histogram oriented gradient features, and aggregate channel features with AdaBoost classifier. In this proposed system, an adaptive attention system based on the convolutional neural network GoogleNet architecture is developed. Hence efficiency in human detection and monitoring is increased and the central processing unit works faster. Using different data (UAV123, UAV123@10fps, COCO, OpenImagesV6) the most efficient performance is obtained with 97.4% accuracy. In addition, up to 75% savings are achieved with efficient use of the central processing unit. The model in this study is a suitable model for unmanned aerial vehicles, autonomous systems that carry out search and rescue activities, especially close-range target tracking in defense systems.


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References Weight

Web of Science® Citations for all references: 47,133 TCR
SCOPUS® Citations for all references: 83,694 TCR

Web of Science® Average Citations per reference: 1,386 ACR
SCOPUS® Average Citations per reference: 2,462 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-07-19 09:12 in 208 seconds.




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