JOURNAL ARTICLE

Real Time Object Detection Using YoloReal Time Object Detection Using Yolo

I Ankith

Year: 2021 Journal:   International Journal for Research in Applied Science and Engineering Technology Vol: 9 (11)Pages: 1504-1511   Publisher: International Journal for Research in Applied Science and Engineering Technology (IJRASET)

Abstract

Abstract: Object detection is related to computer vision and involves identifying the kinds of objects that have been detected. It is challenging to detect and classify objects. Recent advances in deep learning have allowed it to detect objects more accurately. In the past, there were several methods or tools used: R-CNN, Fast-RCNN, Faster-RCNN, YOLO, SSD, etc. This research focuses on "You Only Look Once" (YOLO) as a type of Convolutional Neural Network. Results will be accurate and timely when tested. So, we analysed YOLOv3's work by using Yolo3-tiny to detect both image and video objects. Keywords: YOLO, Intersection over Union (IOU), Anchor box, Non-Max Suppression, YOLO application, limitation.

Keywords:
Object detection Computer science Artificial intelligence Convolutional neural network Intersection (aeronautics) Computer vision Object (grammar) Deep learning Pattern recognition (psychology) Geography Cartography

Metrics

4
Cited By
0.56
FWCI (Field Weighted Citation Impact)
8
Refs
0.74
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Computer Science and Engineering
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Neural Network Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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