FPGA-Based Vehicle Detection and Tracking Accelerator
A convolutional neural network-based multiobject detection and tracking algorithm can be applied to vehicle detection and traffic flow statistics, thus enabling smart transportation. Aiming at the problems of the high computational complexity of multiobject detection and tracking algorithms, a large...
Main Authors: | Jiaqi Zhai, Bin Li, Shunsen Lv, Qinglei Zhou |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-02-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/23/4/2208 |
Similar Items
-
Dynamic Tracking Method Based on Improved DeepSORT for Electric Vehicle
by: Kai Zhu, et al.
Published: (2024-08-01) -
A Target Re-Identification Method Based on Shot Boundary Object Detection for Single Object Tracking
by: Bingchen Miao, et al.
Published: (2023-05-01) -
Detector–Tracker Integration Framework for Autonomous Vehicles Pedestrian Tracking
by: Huanhuan Wang, et al.
Published: (2023-04-01) -
Parking Time Violation Tracking Using YOLOv8 and Tracking Algorithms
by: Nabin Sharma, et al.
Published: (2023-06-01) -
FPGA Implementation of a Deep Learning Acceleration Core Architecture for Image Target Detection
by: Xu Yang, et al.
Published: (2023-03-01)