A New Vehicle Tracking System with R-CNN and Random Forest Classifier for Disaster Management Platform to Improve Performance-Reference-Cited by-同舟云学术

A New Vehicle Tracking System with R-CNN and Random Forest Classifier for Disaster Management Platform to Improve Performance

Published:2022-10-10 Issue: Volume: Page:
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Container-title:2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)
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Author:

Vinoth Kumar T.¹,Yeruva Ajay Reddy²,Kumar Sumeet³,Gangodkar Durgaprasad⁴,L N Rao A⁵,Chaturvedi Prateek⁶

Affiliation:

1. RVS College of Engineering and Technology,Coimbatore,India

2. Independent Researcher,Pleasanton,CA,USA

3. Multani Mal Modi College,Department of CSE,Patiala,India

4. Graphic Era Deemed to be University, Graphic Era Hill University,Department of CSE,Dehradun,Uttarakhand,India

5. Lloyd Institute of Engineering and Technology,Department of CSE,Greater Noida,Uttar Pradesh,India

6. Amity University,Greater Noida,Uttar Pradesh,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9987725/9987727/09988024.pdf?arnumber=9988024

Reference27 articles.

1. Energy-Efficient UART Design on FPGA Using Dynamic Voltage Scaling for Green Communication in Industrial Sector

2. Vehicle class recognition from video-based on 3d curve probes;han;2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance,0

3. Selective Search for Object Recognition

4. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

5. A Generic Deformable Model for Vehicle Recognition.

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