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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:

A hybrid method for fire detection based on spatial and temporal patterns
Pedro Vinícius Almeida Borges de Venâncio, Roger Júnio Campos, Tamires Martins Rezende, et al.
Neural Computing and Applications (2023) Vol. 35, Iss. 13, pp. 9349-9361
Closed Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

ESFD-YOLOv8n: Early Smoke and Fire Detection Method Based on an Improved YOLOv8n Model
Dilshodjon Mamadaliev, Philippe Lyonel Mbouembe Touko, Jae Ho Kim, et al.
Fire (2024) Vol. 7, Iss. 9, pp. 303-303
Open Access | Times Cited: 13
YOLO-Based Models for Smoke and Wildfire Detection in Ground and Aerial Images
Leon Augusto Okida Gonçalves, Rafik Ghali, Moulay A. Akhloufi
Fire (2024) Vol. 7, Iss. 4, pp. 140-140
Open Access | Times Cited: 12
Domain-free fire detection using the spatial–temporal attention transform of the YOLO backbone
Sangwon Kim, In‐Su Jang, Byoung Chul Ko
Pattern Analysis and Applications (2024) Vol. 27, Iss. 2
Closed Access | Times Cited: 10
Fire and smoke detection from videos: A literature review under a novel taxonomy
Diego Gragnaniello, Antonio Greco, Carlo Sansone, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124783-124783
Open Access | Times Cited: 9
FLAME: fire detection in videos combining a deep neural network with a model-based motion analysis
Diego Gragnaniello, Antonio Greco, Carlo Sansone, et al.
Neural Computing and Applications (2025)
Open Access | Times Cited: 1
Video Fire Detection Methods Based on Deep Learning: Datasets, Methods, and Future Directions
C Jin, Tao Wang, Naji Alhusaini, et al.
Fire (2023) Vol. 6, Iss. 8, pp. 315-315
Open Access | Times Cited: 23
Enhancing real-time fire detection: an effective multi-attention network and a fire benchmark
Taimoor Ashraf Khan, Zulfiqar Ahmad Khan, Chang Choi
Neural Computing and Applications (2023)
Closed Access | Times Cited: 14
Vision-Based Construction Safety Monitoring Utilizing Temporal Analysis to Reduce False Alarms
Syed Farhan Alam Zaidi, Jaehun Yang, Muhammad Sibtain Abbas, et al.
Buildings (2024) Vol. 14, Iss. 6, pp. 1878-1878
Open Access | Times Cited: 5
Efficient Deep Learning-Based Fire and Smoke Detection with YOLO Architecture
Szidónia Lefkovits, Nicolae Lupușor, László Lefkovits
Lecture notes in networks and systems (2025), pp. 132-147
Closed Access
Video Fire Recognition Using Zero-shot Vision-language Models Guided by a Task-aware Object Detector
Diego Gragnaniello, Antonio Greco, Carlo Sansone, et al.
ACM Transactions on Multimedia Computing Communications and Applications (2025)
Open Access
From smoke to fire: A forest fire early warning and risk assessment model fusing multimodal data
Peter J. Jin, Pengle Cheng, Xiaodong Liu, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 152, pp. 110848-110848
Closed Access
An innovative hybrid method utilizing fused transformer-based deep features and deep neural networks for detecting forest fires
Kemal Akyol
Advances in Space Research (2025)
Closed Access
YOLO-SAD for fire detection and localization in real-world images
Ruixin Yang, Jun Jiang, Feiyang Liu, et al.
Digital Signal Processing (2025), pp. 105320-105320
Closed Access
Complex Scenes Fire Object Detection Based on Feature Fusion and Channel Attention
Xinrong Cao, Jincai Wu, Jian Chen, et al.
Arabian Journal for Science and Engineering (2024)
Closed Access | Times Cited: 3
Weather-informed lightweight framework for robust smoke video detection using BFBlock-enhanced feature extraction
Xinying Li, Pengle Cheng, Xiaodong Liu, et al.
Signal Image and Video Processing (2025) Vol. 19, Iss. 5
Closed Access
FIRESTART: Fire Ignition Recognition with Enhanced Smoothing Techniques and Real-Time Tracking
Luca Zedda, Andrea Loddo, Cecilia Di Ruberto
Lecture notes in computer science (2024), pp. 282-293
Closed Access | Times Cited: 2
ONFIRE Contest 2023: Real-Time Fire Detection on the Edge
Diego Gragnaniello, Antonio Greco, Carlo Sansone, et al.
Lecture notes in computer science (2024), pp. 273-281
Closed Access | Times Cited: 2
Rapid Fire Detection with Early Exiting
Grace Vincent, Laura Desantis, Ethan Patten, et al.
Lecture notes in computer science (2024), pp. 294-301
Closed Access | Times Cited: 2
A 6G-Enabled Edge-Assisted Internet of Drone Things Ecosystem for Fire Detection
Amartya Mukherjee, Subroto Rakshit, Ayan Kumar Panja, et al.
Lecture notes in networks and systems (2024), pp. 13-25
Closed Access | Times Cited: 2
Improving Computer Vision-Based Wildfire Smoke Detection by Combining SE-ResNet with SVM
Xin Wang, Jinxin Wang, Lin-Lin Chen, et al.
Processes (2024) Vol. 12, Iss. 4, pp. 747-747
Open Access | Times Cited: 1
Fire and Smoke Detection with Burning Intensity Representation
Xiaoyi Han, Yanfei Wu, Nan Pu, et al.
(2024), pp. 1-8
Closed Access | Times Cited: 1
DATFNets-dynamic adaptive assigned transformer network for fire detection
Zuoxin Wang, Xiaohu Zhao, Dunqing Li
Complex & Intelligent Systems (2024) Vol. 10, Iss. 4, pp. 5703-5720
Open Access
DG-YOLO: A Novel Efficient Early Fire Detection Algorithm Under Complex Scenarios
Xuefeng Jiang, Liuquan Xu, Xianjin Fang
Fire Technology (2024)
Closed Access
A Study on Flame Detection Method Combining Visible Light and Thermal Infrared Multimodal Images
Wei Sun, Jiansheng Liu, Feng Wang, et al.
Fire Technology (2024)
Closed Access
Onfire 2023 Contest: what did we learn about real time fire detection from cameras?
Diego Gragnaniello, Antonio Greco, Carlo Sansone, et al.
Journal of Ambient Intelligence and Humanized Computing (2024) Vol. 16, Iss. 1, pp. 253-264
Closed Access
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