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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:

Incidents1M: a Large-Scale Dataset of Images With Natural Disasters, Damage, and Incidents
Ethan Weber, Dim P. Papadopoulos, Àgata Lapedriza, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2022), pp. 1-14
Open Access | Times Cited: 24

Showing 24 citing articles:

An Ensemble Learning Approach With Attention Mechanism for Detecting Pavement Distress and Disaster-Induced Road Damage
Shouxing Wang, Hongzan Jiao, Xin Su, et al.
IEEE Transactions on Intelligent Transportation Systems (2024) Vol. 25, Iss. 10, pp. 13667-13681
Closed Access | Times Cited: 8
A Machine learning approach for Post-Disaster data curation
Sun Ho Ro, Yitong Li, Jie Gong
Advanced Engineering Informatics (2024) Vol. 60, pp. 102427-102427
Closed Access | Times Cited: 6
On Transfer Learning for Building Damage Assessment from Satellite Imagery in Emergency Contexts
Isabelle Bouchard, Marie‐Ève Rancourt, Daniel Aloise, et al.
Remote Sensing (2022) Vol. 14, Iss. 11, pp. 2532-2532
Open Access | Times Cited: 26
Classification and detection of natural disasters using machine learning and deep learning techniques: A review
Kibitok Abraham, Moataz M. Abdelwahab, Mohammed Abo‐Zahhad
Earth Science Informatics (2023) Vol. 17, Iss. 2, pp. 869-891
Closed Access | Times Cited: 12
Leveraging CNNs and Ensemble Learning for Automated Disaster Image Classification
Archit Rathod, Veer Pariawala, Mokshit Surana, et al.
Algorithms for intelligent systems (2024), pp. 311-326
Closed Access | Times Cited: 2
A social context-aware graph-based multimodal attentive learning framework for disaster content classification during emergencies
S. Dar, Mohammad Zia Ur Rehman, Karan Bais, et al.
Expert Systems with Applications (2024) Vol. 259, pp. 125337-125337
Open Access | Times Cited: 2
Building a Vision Transformer-Based Damage Severity Classifier with Ground-Level Imagery of Homes Affected by California Wildfires
Kevin Luo, Ie‐Bin Lian
Fire (2024) Vol. 7, Iss. 4, pp. 133-133
Open Access | Times Cited: 1
Natural Disaster Twitter Data Classification Using CNN and Logistic Regression
S. V. Parasher, Prahlada Varada Mittal, Sejal Karki, et al.
Lecture notes in networks and systems (2024), pp. 681-692
Closed Access | Times Cited: 1
Multimodal Social Sensing for the Spatio-Temporal Evolution and Assessment of Nature Disasters
Yu Chen, Zhiguo Wang
Sensors (2024) Vol. 24, Iss. 18, pp. 5889-5889
Open Access | Times Cited: 1
Leveraging local neighborhood features in 3D unstructured point cloud data for geometry-based automated damage delineation
Madhu Areti, Zohaib Hasnain
Automation in Construction (2024) Vol. 162, pp. 105393-105393
Closed Access | Times Cited: 1
Leveraging involution and convolution in an explainable building damage detection framework
Seyd Teymoor Seydi, Mahdi Hasanlou, Jocelyn Chanussot, et al.
European Journal of Remote Sensing (2023) Vol. 56, Iss. 1
Open Access | Times Cited: 3
Unsupervised learning framework for region-based damage assessment on xBD, a large satellite imagery
Prahlada Varada Mittal, Rishabh Bafna, Ankush Mittal
Natural Hazards (2023) Vol. 118, Iss. 2, pp. 1619-1643
Open Access | Times Cited: 2
CrisisViT: A Robust Vision Transformer for Crisis Image Classification
Zijun Long, Richard McCreadie, Muhammad Imran
Proceedings of the ... International ISCRAM Conference (2023)
Open Access | Times Cited: 2
Deep-Disaster: Unsupervised Disaster Detection and Localization Using Visual Data
Soroor Shekarizadeh, Razieh Rastgoo, Saif Al‐Kuwari, et al.
2022 26th International Conference on Pattern Recognition (ICPR) (2022), pp. 2814-2821
Open Access | Times Cited: 4
CrashCar101: Procedural Generation for Damage Assessment
Jens Parslov, Erik Riise, Dim P. Papadopoulos
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (2024), pp. 4612-4622
Open Access
DisasterRes-Net: A framework for analyzing social media images in disaster response
Tanu Gupta, Sudip Roy
International Journal of Disaster Risk Reduction (2024), pp. 105119-105119
Closed Access
Building a ViT-Based Damage Severity Classifier with Ground- Level Imagery of Homes Impacted by California Wildfires
Kevin Luo, Ie‐Bin Lian
(2024)
Open Access
OptimalNN: A Neural Network Architecture to Monitor Chemical Contamination in Cancer Alley
Uchechukwu Leo Udeji, Martin Margala
Journal of Low Power Electronics and Applications (2024) Vol. 14, Iss. 2, pp. 33-33
Open Access
Development of a Flood Impact Assessment Framework Integrating Crowdsourced Data and Geospatial Information for Data Sparse Urban Regions
Padmini Ponukumati, Satish Kumar Regonda
International Journal of Disaster Risk Reduction (2024) Vol. 116, pp. 105048-105048
Closed Access
Image-Based Criticality-Aware Fire Detection
Alina Arshad, Jawwad Ahmed Shamsi, Muhammad Burhan Khan, et al.
(2024), pp. 1-6
Closed Access
Role of Social Media Imagery in Disaster Informatics
Firoj Alam, Kashif Ahmad, Md. Arid Hasan, et al.
International Handbook of Disaster Research (2023), pp. 1-21
Closed Access | Times Cited: 1
Machine Learning Models for Mining Social Media Data for Effective Natural Disaster Assessment
Prahlada Varada Mittal, Sejal Karki, S. V. Parasher, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
Unsupervised learning framework for region based damage assessment on xBD, a large satellite imagery
Prahlada Varada Mittal, Rishabh Bafna
Research Square (Research Square) (2023)
Open Access
Role of Social Media Imagery in Disaster Informatics
Firoj Alam, Kashif Ahmad, Md. Arid Hasan, et al.
International Handbook of Disaster Research (2023), pp. 531-551
Closed Access
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