ArticleSensors (Basel, Switzerland)2022
Air Pollution Detection Using a Novel Snap-Shot Hyperspectral Imaging Technique.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Recent Advances in Counterfeit Art, Document, Photo, Hologram, and Currency Detection Using Hyperspectral Imaging.Sensors (Basel, Switzerland) · 2022Pooled it
- Identification of Acoustic Emission Spectrograms from Limestone Fracturing Based on a Novel Deep Learning Model.Sensors (Basel, Switzerland) · 2026Article
- Precision Imaging for Early Detection of Esophageal Cancer.Bioengineering (Basel, Switzerland) · 2025Article
- Evaluation of Band Selection for Spectrum-Aided Visual Enhancer (SAVE) for Esophageal Cancer Detection.Journal of Cancer · 2025Article
- Systematic Meta-Analysis of Computer-Aided Detection of Breast Cancer Using Hyperspectral Imaging.Bioengineering (Basel, Switzerland) · 2024Review
- Performance Evaluation of an Object Detection Model Using Drone Imagery in Urban Areas for Semi-Automatic Artificial Intelligence Dataset Construction.Sensors (Basel, Switzerland) · 2024Article
- Spectrum aided vision enhancer enhances mucosal visualization by hyperspectral imaging in capsule endoscopy.Scientific reports · 2024Article
- Technological Frontiers in Brain Cancer: A Systematic Review and Meta-Analysis of Hyperspectral Imaging in Computer-Aided Diagnosis Systems.Diagnostics (Basel, Switzerland) · 2024Review
- Large-Area Film Thickness Identification of Transparent Glass by Hyperspectral Imaging.Sensors (Basel, Switzerland) · 2024Article
- Application of Event Cameras and Neuromorphic Computing to VSLAM: A Survey.Biomimetics (Basel, Switzerland) · 2024Review
- Review of the application of the most current sophisticated image processing methods for the skin cancer diagnostics purposes.Archives of dermatological research · 2024Review
- A densely connected causal convolutional network separating past and future data for filling missing PMHeliyon · 2024Article
- Assessment of hyperspectral imaging and CycleGAN-simulated narrowband techniques to detect early esophageal cancer.Scientific reports · 2023Article
- Systematic meta-analysis of computer-aided detection to detect early esophageal cancer using hyperspectral imaging.Biomedical optics express · 2023Article
- Optical Identification of Diabetic Retinopathy Using Hyperspectral Imaging.Journal of personalized medicine · 2023Article
- Automatic Counterfeit Currency Detection Using a Novel Snapshot Hyperspectral Imaging Algorithm.Sensors (Basel, Switzerland) · 2023Article
- Classification of Skin Cancer Using Novel Hyperspectral Imaging Engineering via YOLOv5.Journal of clinical medicine · 2023Article
- Mutual Information-Driven Feature Reduction for Hyperspectral Image Classification.Sensors (Basel, Switzerland) · 2023Article
- Statistical Analysis of the Impact of COVID-19 on PMSensors (Basel, Switzerland) · 2022Article
- Intelligent Identification of Early Esophageal Cancer by Band-Selective Hyperspectral Imaging.Cancers · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Air pollution has emerged as a global problem in recent years. Particularly, particulate matter (PM2.5) with a diameter of less than 2.5 μm can move through the air and transfer dangerous compounds to the lungs through human breathing, thereby creating major health issues. This research proposes a large-scale, low-cost solution for detecting air pollution by combining hyperspectral imaging (HSI) technology and deep learning techniques. By modeling the visible-light HSI technology of the aerial camera, the image acquired by the drone camera is endowed with hyperspectral information. Two methods are used for the classification of the images. That is, 3D Convolutional Neural Network Auto Encoder and principal components analysis (PCA) are paired with VGG-16 (Visual Geometry Group) to find the optical properties of air pollution. The images are classified into good, moderate, and severe based on the concentration of PM2.5 particles in the images. The results suggest that the PCA + VGG-16 has the highest average classification accuracy of 85.93%.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.