Filters








679 Hits in 9.8 sec

A Machine learning approach for rapid disaster response based on multi-modal data. The case of housing shelter needs [article]

Karla Saldana Ochoa, Tina Comes
2021 arXiv   pre-print
Based on a database of 19 characteristics for more than 200 disasters worldwide, a fusion approach at the decision level was used.  ...  To address this gap and make a headway in comprehensive assessments, this paper proposes a machine learning workflow that aims to fuse and rapidly analyse multimodal data.  ...  ACKNOWLEDGMENTS The authors would like to thank the Reviewers and Editor for their helpful comments and constructive suggestions.  ... 
arXiv:2108.00887v2 fatcat:oot7ittlsjhxbm7ouimlpurzza

EOPEN: Open interoperable platform for unified access and analysis of earth observation data

Guido Vingione, Gabriella Scarpino, Laurence Marzell, Tudor Pettengell, Ilias Gialampoukidis, Stelios Andreadis, Stefanos Vrochidis, Ioannis Kompatsiaris, Bernard Valentin, Leslie Gale, Woo-Kyun Lee, Wona Lee (+10 others)
2019 Zenodo  
EOPEN (https://eopen-project.eu/) is a project which has received funding from the European Union's Horizon 2020 research and innovation programme under the topic EO Big Data Shift in 2017 and has a duration  ...  In this work, we present the concept of the project, its objectives and the lessons learnt after almost one year of project lifetime, as a follow-up to our previous project presentation at ESA BiDS'17  ...  All these heterogeneous sources of information are combined, through multimodal fusion, to semantically interpret the content of EO data resulting in efficient decision-making and visualisation in line  ... 
doi:10.5281/zenodo.2539266 fatcat:jrkbn6v6qfbvhogo55idaqd6iy

Automatic analysis of social media images to identify disaster type and infer appropriate emergency response

Amna Asif, Shaheen Khatoon, Md Maruf Hasan, Majed A. Alshamari, Sherif Abdou, Khaled Mostafa Elsayed, Mohsen Rashwan
2021 Journal of Big Data  
type of emergency response for a given disaster.  ...  algorithms to automate the emergency response decision-making process.  ...  Acknowledgements The authors extend their appreciation to the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number 523.  ... 
doi:10.1186/s40537-021-00471-5 fatcat:qnb7xej6cbhurldhk5tifcs4ou

Front Matter: Volume 11756

Lynne L. Grewe, Erik P. Blasch, Ivan Kadar
2021 Signal Processing, Sensor/Information Fusion, and Target Recognition XXX  
for dynamic search INFORMATION FUSION METHODOLOGIES AND APPLICATIONS IV 0R Anomaly detection with noisy and missing data using a deep learning architecture 11756 0S Fairness-by-design Dempster-Shafer  ...  These two-number sets start with 00, 01, 02, 03, 04, 0M Risk-based security: from theory to practice INFORMATION FUSION METHODOLOGIES AND APPLICATIONS III 0N Anomaly detection of unstructured big data  ...  Data Multi-INT Knowledge Fusion and Reasoning Social Network Analysis Joint Data Learning Background and Motivation • Huge growth in social media, especially online social networking services,  ... 
doi:10.1117/12.2598593 fatcat:5afkuwltljctxayaup2rz2njly

Project rescue: challenges in responding to the unexpected

Sharad Mehrotra, C. T. Butts, D. Kalashnikov, Nalini Venkatasubramanian, Ramesh R. Rao, G. Chockalingam, R. Eguchi, B. J. Adams, C. Huyck, Simone Santini, Raimondo Schettini
2003 Internet Imaging V  
store, analyze, interpret, share and disseminate data.  ...  Organizational Response: In this phase, emergency resources are deployed and organizational decisions are disseminated to crisis-workers and the population at large.  ...  integration of imagery with decision-making methodologies ACKNOWLEDGEMENTS We would like to acknowledge all the members of the RESCUE project research team (http://www.itr-rescue.org) and our government  ... 
doi:10.1117/12.537805 fatcat:6jlkux62cbh5nldqtq3hxajkru

Multimodal Classification: Current Landscape, Taxonomy and Future Directions [article]

William C. Sleeman IV, Rishabh Kapoor, Preetam Ghosh
2021 arXiv   pre-print
Many of the most difficult aspects of unimodal classification have not yet been fully addressed for multimodal datasets including big data, class imbalance, and instance level difficulty.  ...  Multimodal classification research has been gaining popularity in many domains that collect more data from multiple sources including satellite imagery, biometrics, and medicine.  ...  The authors of [115] built a classification network for social media based sentiment analysis using image and text.  ... 
arXiv:2109.09020v1 fatcat:yagsbnxeefcpneqwgflrxxioqa

Distributed Fusion of Heterogeneous Remote Sensing and Social Media Data: A Review and New Developments

Jun Li, Zhenjie Liu, Xinya Lei, Lizhe Wang
2021 Proceedings of the IEEE  
A new distributed fusion framework that can accelerate the fusion of heterogeneous remote sensing and social media data is proposed by decomposing large data sets into small ones and processing them in  ...  social media data).  ...  monitoring and decision-making.  ... 
doi:10.1109/jproc.2021.3079176 fatcat:gk2xqgsipjfr7kfanauymtk724

Disaster Image Classification by Fusing Multimodal Social Media Data

Zhiqiang Zou, Hongyu Gan, Qunying Huang, Tianhui Cai, Kai Cao
2021 ISPRS International Journal of Geo-Information  
Useful information could be mined from these multimodal data to enable situational awareness and to support decision making during disasters.  ...  However, the multimodal data collected from social media contain a lot of irrelevant and misleading content that needs to be filtered out.  ...  Meanwhile, we thank the editors and reviewers for their valuable comments. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijgi10100636 fatcat:izygbdfjvzanncziwqlcjk7utu

Multimodal Classification: Current Landscape, Taxonomy and Future Directions

William C. Sleeman Iv, Rishabh Kapoor, Preetam Ghosh
2022 ACM Computing Surveys  
Many of the most difficult aspects of unimodal classification have not yet been fully addressed for multimodal datasets including big data, class imbalance, and instance level difficulty.  ...  Multimodal classification research has been gaining popularity with new datasets in domains such as satellite imagery, biometrics, and medicine.  ...  In the work by Illendula and Sheth [46] , a model was built to predict emotion from social media posts using image and text.  ... 
doi:10.1145/3543848 fatcat:ejigpgm5gnabvc4jrb3nml5l4y

Social Media Alert and Response to Threats to Citizens

Nabil Adam, Jayan Eledath, Sharad Mehrotra, Nalini Venkatasubramanian
2012 Proceedings of the 8th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing  
Social media, such as blogs, Twitter, and information portals, have emerged as the dominant communication mechanism of society.  ...  These components include mechanisms to model event level semantic information, a platform for implementing multi-sensor fusion, mechanisms for estimating the veracity of information, data cleaning to reduce  ...  Their contributions to the concept, design, and architecture of Smart-C are gratefully acknowledged.  ... 
doi:10.4108/icst.collaboratecom.2012.250713 dblp:conf/colcom/AdamEMV12 fatcat:zhcioeeclrc63bhdu2lmwjvxuu

Foundations and Recent Trends in Multimodal Machine Learning: Principles, Challenges, and Open Questions [article]

Paul Pu Liang, Amir Zadeh, Louis-Philippe Morency
2022 arXiv   pre-print
With the recent interest in video understanding, embodied autonomous agents, text-to-image generation, and multisensor fusion in application domains such as healthcare and robotics, multimodal machine  ...  foundations of multimodal machine learning.  ...  Lyu for helpful discussions and feedback on initial versions of this paper.  ... 
arXiv:2209.03430v1 fatcat:ne5vfyz67rgxzmvdiv37hpuare

FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding

Maryam Rahnemoonfar, Tashnim Chowdhury, Argho Sarkar, Debvrat Varshney, Masoud Yari, Robin Murphy
2021 IEEE Access  
Available post-disaster damage assessment datasets [8] - [11] mainly contain satellite images and images collected from social media. Satellite images are low in resolution and costly.  ...  Nguyen et al. proposed an extension of AIDR system [21] to collect data from social media in [30] .  ... 
doi:10.1109/access.2021.3090981 fatcat:wacd4jsapzfuhhu5kjvkl3ab2m

Machine Learning in Disaster Management: Recent Developments in Methods and Applications

Vasileios Linardos, Maria Drakaki, Panagiotis Tzionas, Yannis L. Karnavas
2022 Machine Learning and Knowledge Extraction  
assessment and post-disaster response as well as cases studies.  ...  Furthermore, some recently developed ML and DL applications for disaster management have been analyzed. A discussion of the findings is provided as well as directions for further research.  ...  Effective decision making by emergency responders and other decision makers can be facilitated by the information posted online on social media platforms such as Twitter.  ... 
doi:10.3390/make4020020 fatcat:wcdrh23k5ja6tdqlyhl7erobey

Multisource and Multitemporal Data Fusion in Remote Sensing [article]

Pedram Ghamisi, Behnood Rasti, Naoto Yokoya, Qunming Wang, Bernhard Hofle, Lorenzo Bruzzone, Francesca Bovolo, Mingmin Chi, Katharina Anders, Richard Gloaguen, Peter M. Atkinson, Jon Atli Benediktsson
2018 arXiv   pre-print
There are a huge number of research works dedicated to multisource and multitemporal data fusion, but the methods for the fusion of different modalities have expanded in different paths according to each  ...  Multisource data fusion has, therefore, received enormous attention from researchers worldwide for a wide variety of applications.  ...  In this case, social media data can have diverse types, such as images, texts and so on, such that different types of the social media data can build different deep neural networks for further decision  ... 
arXiv:1812.08287v1 fatcat:hmojxdoaybc6vjeto5s3x7b6z4

Multimodal hyperspectral remote sensing: an overview and perspective

Yanfeng Gu, Tianzhu Liu, Guoming Gao, Guangbo Ren, Yi Ma, Jocelyn Chanussot, Xiuping Jia
2021 Science China Information Sciences  
Through the analysis of development trend of hyperspectral imaging and current research situation, we hope to provide a direction for future research on multimodal hyperspectral remote sensing.  ...  hyperspectral imaging modes are carried out from the following four aspects: fundamental principle of new mode of hyperspectral imaging, corresponding scientific data acquisition, data processing and application  ...  Those researches could be treated as general multimodal remote sensing, which focus on how to integrate the social media data to improve interpretation ability of remote sensing data.  ... 
doi:10.1007/s11432-020-3084-1 fatcat:tivcc4l5efh5zg62t37stswqgu
« Previous Showing results 1 — 15 out of 679 results