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On Estimating Air Pollution from Photos Using Convolutional Neural Network

Published: 01 October 2016 Publication History

Abstract

Air pollution has raised people's intensive concerns especially in developing countries such as China and India. Different from using expensive or unreliable methods like sensor-based or social network based one, photo based air pollution estimation is a promising direction, while little work has been done up to now. Focusing on this immediate problem, this paper devises an effective convolutional neural network to estimate air's quality based on photos. Our method is comprised of two ingredients: first a negative log-log ordinal classifier is devised in the last layer of the network, which can improve the ordinal discriminative ability of the model. Second, as a variant of the Rectified Linear Units (ReLU), a modified activation function is developed for photo based air pollution estimation. This function has been shown it can alleviate the vanishing gradient issue effectively. We collect a set of outdoor photos and associate the pollution levels from official agency as the ground truth. Empirical experiments are conducted on this real-world dataset which shows the capability of our method.

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cover image ACM Conferences
MM '16: Proceedings of the 24th ACM international conference on Multimedia
October 2016
1542 pages
ISBN:9781450336031
DOI:10.1145/2964284
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 01 October 2016

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Author Tags

  1. CNN
  2. air pollution

Qualifiers

  • Short-paper

Funding Sources

  • National Natural Science Foundation of China
  • the Fundamental Research Funds for the Central Universities
  • SRF for ROCS SEM
  • China Postdoctoral Science Foundation Funded Project

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MM '16
Sponsor:
MM '16: ACM Multimedia Conference
October 15 - 19, 2016
Amsterdam, The Netherlands

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MM '16 Paper Acceptance Rate 52 of 237 submissions, 22%;
Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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  • (2025)Indoor and urban air quality: control and improvementsAir Pollution, Air Quality, and Climate Change10.1016/B978-0-443-23816-1.00010-0(103-173)Online publication date: 2025
  • (2025)Data-driven analysis and predictive modelling of hourly Air Quality Index (AQI) using deep learning techniques: a case study of Azamgarh, IndiaTheoretical and Applied Climatology10.1007/s00704-024-05304-y156:1Online publication date: 8-Jan-2025
  • (2025)A Survey on Image-Based Air Quality EstimationBig Data and Internet of Things10.1007/978-3-031-74491-4_10(124-138)Online publication date: 3-Jan-2025
  • (2024)Exploring Indoor Air Quality Dynamics in Developing Nations: A Perspective from IndiaACM Journal on Computing and Sustainable Societies10.1145/36856942:3(1-40)Online publication date: 2-Aug-2024
  • (2024) Deep-Learning-Based Multi-Timestamp Multi-Location PM 2.5 Prediction: Verification by Using a Mobile Monitoring System With an IoT Framework Deployed in the Urban Zone of a Metropolitan Area IEEE Internet of Things Journal10.1109/JIOT.2023.332286211:5(8815-8837)Online publication date: 1-Mar-2024
  • (2024)A Hybrid Decision-Tree and ANN Learning Model for Air Contamination Forecasting2024 Third International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)10.1109/ICSTSN61422.2024.10670902(1-5)Online publication date: 18-Jul-2024
  • (2024)Advancing river monitoring using image-based techniques: challenges and opportunitiesHydrological Sciences Journal10.1080/02626667.2024.233384669:6(657-677)Online publication date: 22-Apr-2024
  • (2024)Transforming air pollution management in India with AI and machine learning technologiesScientific Reports10.1038/s41598-024-71269-714:1Online publication date: 2-Sep-2024
  • (2024)Uncovering local aggregated air quality index with smartphone captured images leveraging efficient deep convolutional neural networkScientific Reports10.1038/s41598-023-51015-114:1Online publication date: 18-Jan-2024
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