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About Real-Time Multiple Object Tracking Using Deep Learning Methods2021
This document summarizes a research paper on real-time multiple object tracking using deep learning methods. The paper introduces a modified version of the Deep SORT algorithm that considers an object tracked if detected in a set of previous frames. This modified Deep SORT is coupled with YOLO object detection and evaluated on traffic videos. The results show the modified Deep SORT framework has good performance and improvements over the original Deep SORT algorithm. The paper also presents a new vehicle dataset for multiple object tracking evaluation.
Detailed Information
Author: | ['sadeq'] |
---|---|
Publication Year: | 2024 |
Pages: | 30 |
Language: | English |
Format: | |
Price: | FREE |
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