Visual attention-based comparative study on disaster detection from social media images

Keywords

• flood disaster
• social media images
• disaster detection
• InceptionResNetV2
• visual attention
• natural disasters
• VGG16
• InceptionV3
• fire disaster
• man-made disasters

CCDS Authors

Prof. M Ashraful Amin, PhD

Prof. M Ashraful Amin, PhD

• Founder Director, CCDS
• Director, AI/ML, HCI & DS Wings

Professor

+1 more affiliation

Department of Information Sciences and Technology

George Mason University, USA

Published at

ACL, CHI, UbiComp, ECAI, WACV, PAKDD, IJCNN, ICPR, ICIP, HCII, CLEF, BLP, Scientific Reports, JMIR, IEEE Access, Smart Agricultural Technology, Frontiers in Computational Neuroscience, Diabetes Research and Clinical Practice, PLOS ONE

Research Interests

Machine Learning, Cognitive & Vision Science, Cybernetics, Surveillance & Security, ICT in Education, Health, & Agriculture, Human-Computer Interaction, Internet of Things, Robotics

Amin Ahsan Ali, PhD

Amin Ahsan Ali, PhD

• Director, AI/ML Wing

Professor

Department of Computer Science and Engineering

Independent University, Bangladesh

Published at

ACL, CHI, UbiComp, ECCV, IJCAI, ECAI, WACV, IPSN, PAKDD, LREC, IJCNN, ICPR, ICIP, BEA, BLP, ICMLA, Scientific Reports, Scientific Data, Pattern Recognition, Information Sciences, Ad Hoc Networks, Drug and Alcohol Dependence, PLOS ONE

Research Interests

Artificial Intelligence, Machine Learning

References

1. 1.Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, Zbigniew Wojna. (2016). Rethinking the Inception Architecture for Computer Vision. , 2818–2826[10.1109/cvpr.2016.308]
2. 2.Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alexander A. Alemi. (2017). Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning. [10.1609/aaai.v31i1.11231]
3. 3.Bolei Zhou, Aditya Khosla, Àgata Lapedriza, Aude Oliva, Antonio Torralba. (2016). Learning Deep Features for Discriminative Localization. , 2921–2929[10.1109/cvpr.2016.319]
4. 4.Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alexander A. Alemi. (2017). Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 31(1)[10.1609/aaai.v31i1.11231]
5. 5.Xiangyu Zhang, Jianhua Zou, Kaiming He, Jian Sun. (2015). Accelerating Very Deep Convolutional Networks for Classification and Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(10), 1943–1955[10.1109/tpami.2015.2502579]
6. 6.Khan Muhammad, Jamil Ahmad, Sung Wook Baik. (2017). Early fire detection using convolutional neural networks during surveillance for effective disaster management. Neurocomputing, 288, 30–42[10.1016/j.neucom.2017.04.083]
7. 7.Dat T. Nguyen, Ferda Ofli, Muhammad Imran, Prasenjit Mitra. (2017). Damage Assessment from Social Media Imagery Data During Disasters. , 569–576[10.1145/3110025.3110109]
8. 8.Firoj Alam, Muhammad Imran, Ferda Ofli. (2017). Image4Act. , 601–604[10.1145/3110025.3110164]
9. 9.Hussein Mouzannar, Yara Rizk, Mariette Awad. (2018). Damage Identification in Social Media Posts using Multimodal Deep Learning.. ISCRAM
10. 10.Konstantinos Avgerinakis, Anastasia Moumtzidou, Stelios Andreadis, Emmanouil Michail, Ilias Gialampoukidis, Stefanos Vrochidis, Ioannis Kompatsiaris. (2017). Visual and Textual Analysis of Social Media and Satellite Images for Flood Detection @ Multimedia Satellite Task MediaEval 2017.. MediaEval
11. 11.Kashif Ahmad, Amir Sohail, Nicola Conci, Francesco G. B. De Natale. (2018). A Comparative Study of Global and Deep Features for the Analysis of User-Generated Natural Disaster Related Images. , 1–5[10.1109/ivmspw.2018.8448670]
12. 12.Yara Rizk, Hadi S. Jomaa, Mariette Awad, Carlos Castillo. (2019). A computationally efficient multi-modal classification approach of disaster-related Twitter images. , 2050–2059[10.1145/3297280.3297481]
13. 13.M. Ashraful Amin, Mahmood Kazi Mohammed. (2015). Overview of the ImageCLEF 2015 medical clustering task. CLEF (Working Notes)
14. 14.Panagiotis Giannakeris, Konstantinos Avgerinakis, Αναστάσιος Καρακώστας, Stefanos Vrochidis, Ioannis Kompatsiaris. (2018). People and Vehicles in Danger - A Fire and Flood Detection System in Social Media. , 1–5[10.1109/ivmspw.2018.8448732]
15. 15.Saumya Jetley, Nicholas A. Lord, Namhoon Lee, Philip H. S. Torr. (2018). Learn To Pay Attention. arXiv (Cornell University)[10.48550/arxiv.1804.02391]

Cited By

1. 1.Nilani Algiriyage, Raj Prasanna, Kristin Stock, Emma E. H. Doyle, David Johnston. (2021). Multi-source Multimodal Data and Deep Learning for Disaster Response: A Systematic Review. SN Computer Science, 3(1), 92[10.1007/s42979-021-00971-4]
2. 2.Umair Iqbal, Pascal Perez, Johan Barthelemy. (2021). A process-driven and need-oriented framework for review of technological contributions to disaster management. Heliyon, 7(11), e08405[10.1016/j.heliyon.2021.e08405]
3. 3.Yang Zhang, Ruohan Zong, Lanyu Shang, Dong Wang. (2023). A crowd-AI dynamic neural network hyperparameter optimization approach for image-driven social sensing applications. Knowledge-Based Systems, 278, 110864[10.1016/j.knosys.2023.110864]
4. 4.Nathaniel Sze Yang Tan, Mau-Luen Tham, Sing Yee Chua, Ying Loong Lee. (2024). Accurate and Fast Classification of Natural Disasters using CNN-LSTM and Inference Acceleration. Journal of Communications Software and Systems, 20(1), 58–68[10.24138/jcomss-2023-0129]
5. 5.Abdallah Saleh Ali Shatat, Md. Mobin Akhtar, Abu Sarwar Zamani, Sara Dilshad, Faizan Samdani. (2022). Big Data Driven Map Reduce Framework for Automated Flood Disaster Detection Based on Heuristic-Based Ensemble Learning. Cybernetics & Systems, 55(7), 1757–1791[10.1080/01969722.2022.2145664]
6. 6.Yoonjo Choi, Namhun Kim, Seunghwan Hong, Junsu Bae, Ilsuk Park, Hong-Gyoo Sohn. (2021). Critical Image Identification via Incident-Type Definition Using Smartphone Data during an Emergency: A Case Study of the 2020 Heavy Rainfall Event in Korea. Sensors, 21(10), 3562[10.3390/s21103562]
7. 7.Fatema Tuj Johora Faria, Mukaffi Bin Moin, Busra Kamal Rafa, Swarnajit Saha, Md. Mahfuzur Rahman, Khan Md Hasib, M.F. Mridha. (2025). BanglaCalamityMMD: A comprehensive benchmark dataset for multimodal disaster identification in the low-resource Bangla language. International Journal of Disaster Risk Reduction, 130, 105800[10.1016/j.ijdrr.2025.105800]
8. 8.Xingang Wang, Honglu D. Cheng, Guangzheng Liu, Xiaoyu Liu. (2023). A multimodal resource balancing approach based on cross-attention and bidrectional associative memory networks. , 16, 87[10.1117/12.3010753]