Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile
Articles by Yan Piao
Enhancing Underwater Images of a Bionic Horseshoe Crab Robot Using an Artificial Lateral Inhibition Network
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
A Virtual View Acquisition Technique for Complex Scenes of Monocular Images Based on Layered Depth Images
This is an early access version, the complete PDF, HTML, and XML versions will be available soon. Open AccessArticle by Qi Wang SciProfiles Scilit Preprints.org Google Scholar and Yan Piao SciProfiles Scilit Preprints.org Google Scholar * College of Electronic and Information Engineering, Changchun University of Science and Technology, Changchun 130022, China * Author to whom correspondence should be addressed. Appl. Sci.
Early Smoke Recognition Algorithm for Forest Fires
1. Introduction Forest fires are a major environmental disaster facing forest resources. Once a forest fire occurs, it can quickly get out of control, and then require enormous effort, time, and resources to extinguish. Additionally, forest fires and related combustion processes release large amounts of pollutants into the atmosphere, including CO2, CO, CH4, BC, VOCs, PM2.5, and PM10.
An Improved Forest Smoke Detection Model Based on YOLOv8
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Multi-Object Tracking Based on Re-Identification Enhancement and Associated Correction
1. Introduction Multiple-object tracking (MOT), as a high-level task in computer vision, has been widely applied in various fields such as video surveillance [1,2,3], human behavior recognition, and autonomous driving [4,5,6]. One of the advantages of video-based MOT [7,8,9,10,11,12,13,14] is its ability to accurately localize targets continuously in videos while maintaining their identity information, unchanged, when the appearance or the surrounding environment changes.
Fourier Ptychographic Reconstruction Method of Self-Training Physical Model
Abstract : Fourier ptychographic microscopy is a new microscopic computational imaging technology. A series of low-resolution intensity images are collected by a Fourier ptychographic microscopy system, and high-resolution intensity and phase images are reconstructed from the collected low-resolution images by a reconstruction algorithm. It is a kind of microscopy that can achieve both a large field of view and high resolution.
An Adaptive Partitioning and Multi-Granularity Network for Video-Based Person Re-Identification
This is an early access version, the complete PDF, HTML, and XML versions will be available soon. Open AccessFeature PaperArticle by Bailiang Huang , Yan Piao * and Yanfeng Tang School of Electronic and Information Engineering, Changchun University of Science and Technology, Changchun 130012, China * Author to whom correspondence should be addressed. Appl. Sci.
Show More
loading
Actions
Is this you?
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.Get in touch with Yan
Contact Yan, search articles and posts on X, monitor coverage, and track replies from one place.
Learn more about Muck Rack