JOURNAL ARTICLE

Real Time Object Detection and Tracking Using Deep Learning and OpenCV

G ChandanAyush JainHarsh JainMohana

Year: 2018 Journal:   2018 International Conference on Inventive Research in Computing Applications (ICIRCA)

Abstract

Deep learning has gained a tremendous influence on how the world is adapting to Artificial Intelligence since past few years. Some of the popular object detection algorithms are Region-based Convolutional Neural Networks (RCNN), Faster-RCNN, Single Shot Detector (SSD) and You Only Look Once (YOLO). Amongst these, Faster-RCNN and SSD have better accuracy, while YOLO performs better when speed is given preference over accuracy. Deep learning combines SSD and Mobile Nets to perform efficient implementation of detection and tracking. This algorithm performs efficient object detection while not compromising on the performance.

Keywords:
Artificial intelligence Computer science Object detection Deep learning Convolutional neural network Computer vision Tracking (education) Object (grammar) Detector Single shot Video tracking Pattern recognition (psychology)

Metrics

272
Cited By
11.55
FWCI (Field Weighted Citation Impact)
11
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Neural Network Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Brain Tumor Detection and Classification
Life Sciences →  Neuroscience →  Neurology

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