Reliability verification‐based convolutional neural networks for object tracking-Reference-Cited by-同舟云学术

Reliability verification‐based convolutional neural networks for object tracking

Published:2019-01 Issue:1 Volume:13 Page:175-185
ISSN:1751-9667
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Hu Xiaopeng¹,Li Jingting¹,Yang Yan¹²,Wang Fan¹

Affiliation:

1. School of Computer Science and Technology, Dalian University of TechnologyNo. 2 Linggong Road Ganjingzi DistrictDalian CityPeople's Republic of China

2. School of Computer and Information Technology, Liaoning Normal UniversityNo. 850 Huanghe Road Shahekou DistrictDalian CityPeople's Republic of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2018.5785

Reference38 articles.

1. Simultaneous multi‐vehicle detection and tracking framework with pavement constraints based on machine learning and particle filter algorithm;Wang K.;Chin. J. Mech. Eng.,2014

2. Video Surveillance Based Tracking System

3. Inverse sparse tracker with a locally weighted distance metric;Wang D.;IEEE Trans. Image Process.,2015

4. Robust Visual Tracking via Least Soft-Threshold Squares

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Research on Background Learning Correlation Filtering Algorithm With Multi-Feature Fusion;IEEE Access;2023

2. Improved convolutional neural network‐based quantile regression for regional photovoltaic generation probabilistic forecast;IET Renewable Power Generation;2020-09-24

3. Combining Spatio-Temporal Context and Kalman Filtering for Visual Tracking;Mathematics;2019-11-05

4. Neural network‐based quickprop control algorithm for grid connected solar PV‐DSTATCOM system;IET Renewable Power Generation;2019-08-16