A deep learning-based PM2.5 concentration estimator-Reference-Cited by-同舟云学术

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A deep learning-based PM2.5 concentration estimator

Published:2021-09 Issue: Volume:69 Page:102072
ISSN:0141-9382
Container-title:Displays
language:en
Short-container-title:Displays

Author:

Sun Kezheng,Tang Lijuan,Qian JianSheng,Wang Guangcheng,Lou Cairong

Funder

National Science and Technology Planning Project

Qinglan Project of Jiangsu Province of China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Human-Computer Interaction

Reference34 articles.

1. Prediction of PM2.5 concentration based on weighted bagging and image contrast-sensitive features;Qiao;Stoch. Environ. Res. Risk Assess.,2020

2. Highly efficient picture-based prediction of PM2.5 concentration;Gu;IEEE Trans. Ind. Electron.,2019

3. Extremely efficient PM2.5 estimator based on analysis of saliency and statistics;Zhang;Electron. Lett.,2019

4. Effective and efficient photo-based PM2.5 concentration estimation;Yue;IEEE Trans. Instrum. Meas.,2019

5. Stacked selective ensemble for PM2.5 forecast;Gu;IEEE Trans. Instrum. Meas.,2020

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3. Prediction of atmospheric PM2.5 level by machine learning techniques in Isfahan, Iran;Scientific Reports;2024-01-24

4. PM$$_{2.5}$$ Concentration Measurement Based on Natural Scene Statistics and Progressive Learning;Communications in Computer and Information Science;2024

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