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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Optimising Deep Learning at the Edge for Accurate Hourly Air Quality Prediction
I Nyoman Kusuma Wardana, Julian W. Gardner, Suhaib A. Fahmy
Sensors (2021) Vol. 21, Iss. 4, pp. 1064-1064
Open Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

Air-pollution prediction in smart city, deep learning approach
Abdellatif Bekkar, Badr Hssina, Samira Douzi, et al.
Journal Of Big Data (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 163
At the Confluence of Artificial Intelligence and Edge Computing in IoT-Based Applications: A Review and New Perspectives
Amira Bourechak, Ouarda Zedadra, Mohamed Nadjib Kouahla, et al.
Sensors (2023) Vol. 23, Iss. 3, pp. 1639-1639
Open Access | Times Cited: 109
TinyML: Enabling of Inference Deep Learning Models on Ultra-Low-Power IoT Edge Devices for AI Applications
Norah N. Alajlan, Dina M. Ibrahim
Micromachines (2022) Vol. 13, Iss. 6, pp. 851-851
Open Access | Times Cited: 93
Machine Learning Techniques to Predict the Air Quality Using Meteorological Data in Two Urban Areas in Sri Lanka
Lakindu Mampitiya, Namal Rathnayake, Lee P. Leon, et al.
Environments (2023) Vol. 10, Iss. 8, pp. 141-141
Open Access | Times Cited: 43
Deep-learning architecture for PM2.5 concentration prediction: A review
Shiyun Zhou, Wei Wang, Long Zhu, et al.
Environmental Science and Ecotechnology (2024) Vol. 21, pp. 100400-100400
Open Access | Times Cited: 23
A Hybrid Spatiotemporal Deep Model Based on CNN and LSTM for Air Pollution Prediction
Stefan Tsokov, Milena Lazarova, Adelina Aleksieva-Petrova
Sustainability (2022) Vol. 14, Iss. 9, pp. 5104-5104
Open Access | Times Cited: 45
A Survey of Machine Learning in Edge Computing: Techniques, Frameworks, Applications, Issues, and Research Directions
Oumayma Jouini, Kaouthar Sethom, Abdallah Namoun, et al.
Technologies (2024) Vol. 12, Iss. 6, pp. 81-81
Open Access | Times Cited: 7
Multi-feature fusion and improved BO and IGWO metaheuristics based models for automatically diagnosing the sleep disorders from sleep sounds
Sinem Akyol, Muhammed Yıldırım, Bilal Alataş
Computers in Biology and Medicine (2023) Vol. 157, pp. 106768-106768
Closed Access | Times Cited: 14
Multistation collaborative prediction of air pollutants based on the CNN-BiLSTM model
Yanan Lu, Kun Li
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 40, pp. 92417-92435
Closed Access | Times Cited: 11
Estimation of missing air pollutant data using a spatiotemporal convolutional autoencoder
I Nyoman Kusuma Wardana, Julian W. Gardner, Suhaib A. Fahmy
Neural Computing and Applications (2022) Vol. 34, Iss. 18, pp. 16129-16154
Open Access | Times Cited: 18
Edge AI for Real-Time Anomaly Detection in Smart Homes
Manuel J. C. S. Reis, Carlos Serôdio
Future Internet (2025) Vol. 17, Iss. 4, pp. 179-179
Open Access
Comprehensive survey on air quality monitoring systems based on emerging computing and communication technologies
Mohamed Saifeddine Hadj Sassi, Lamia Chaari Fourati
Computer Networks (2022) Vol. 209, pp. 108904-108904
Closed Access | Times Cited: 16
Split BiRNN for real-time activity recognition using radar and deep learning
Lorin Werthen‐Brabants, Geethika Bhavanasi, Ivo Couckuyt, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 15
TinyML Models for a Low-Cost Air Quality Monitoring Device
I Nyoman Kusuma Wardana, Suhaib A. Fahmy, Julian W. Gardner
IEEE Sensors Letters (2023) Vol. 7, Iss. 11, pp. 1-4
Open Access | Times Cited: 7
A novel bifold-attention-LSTM for analyzing PM2.5 concentration-based multi-station data time series
Andri Pranolo, Xiaofeng Zhou, Yingchi Mao
International Journal of Data Science and Analytics (2024)
Closed Access | Times Cited: 2
Securing constrained IoT systems: A lightweight machine learning approach for anomaly detection and prevention
Zainab Alwaisi, Tanesh Kumar, Erkki Harjula, et al.
Internet of Things (2024), pp. 101398-101398
Open Access | Times Cited: 2
Collaborative Learning at the Edge for Air Pollution Prediction
I Nyoman Kusuma Wardana, Julian W. Gardner, Suhaib A. Fahmy
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 73, pp. 1-12
Closed Access | Times Cited: 5
Air quality index prediction with optimisation enabled deep learning model in IoT application
S. Sivakumar
Environmental Technology (2024), pp. 1-17
Closed Access | Times Cited: 1
Predicting Beijing Air Quality Using Bayesian Optimized CNN-RNN Hybrid Model
Zihan Tu, Zhe Wu
2022 Asia Conference on Algorithms, Computing and Machine Learning (CACML) (2022)
Closed Access | Times Cited: 7
Modeling indoor PM2.5 using Adaptive Dynamic Fuzzy Inference System Tree (ADFIST) on Internet of Things-based sensor network data
Jagriti Saini, Maitreyee Dutta, Gonçalo Marques
Internet of Things (2022) Vol. 20, pp. 100628-100628
Closed Access | Times Cited: 7
IoT-enhanced infant incubator monitoring system with 1D-CNN temperature prediction model
I Komang Agus Ady Aryanto, Dechrit Maneetham, Padma Nyoman Crisnapati
Indonesian Journal of Electrical Engineering and Computer Science (2024) Vol. 34, Iss. 2, pp. 900-900
Open Access | Times Cited: 1
Optimizing a Multispectral-Images-Based DL Model, Through Feature Selection, Pruning and Quantization
Julio Torres-Tello, Seok‐Bum Ko
2022 IEEE International Symposium on Circuits and Systems (ISCAS) (2022), pp. 1352-1356
Closed Access | Times Cited: 6
Prediction of Particulate Matter 2.5 Concentration Using a Deep Learning Model with Time-Frequency Domain Information
Xueming Tang, Nan Wu, Ying Pan
Applied Sciences (2023) Vol. 13, Iss. 23, pp. 12794-12794
Open Access | Times Cited: 3
Enhancing Neonatal Incubator Energy Management and Monitoring through IoT-Enabled CNN-LSTM Combination Predictive Model
I Komang Agus Ady Aryanto, Dechrit Maneetham, Padma Nyoman Crisnapati
Applied Sciences (2023) Vol. 13, Iss. 23, pp. 12953-12953
Open Access | Times Cited: 2
Convolutional attention with roll padding: Classifying PM2.5 concentration levels in the city of Beijing
Rui Gonçalves, Vítor Miguel Ribeiro
Energy (2023) Vol. 289, pp. 130045-130045
Open Access | Times Cited: 2
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