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Leveraging Multimodal Deep Learning For Natural Disaster Event Classification And Its Damage Severity Analysis Through Social Media Posts by Nivedita Kasturi%2c Shashikumar Guruputra Totad%2c Goldina Ghosh
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1Leveraging Multimodal Deep Learning For Natural Disaster Event Classification And Its Damage Severity Analysis Through Social Media Posts
By Nivedita Kasturi, Shashikumar Guruputra Totad, Goldina Ghosh
Accurate and timely information is critical to effectively coordinate disaster response. Due to the diversity and complexity of data sources, it is difficult for traditional methods to classify disaster events and assess damage severity. Previous studies have mainly focused on specific tasks, such as information collection or humanitarian assistance, but have not adequately addressed the assessment of disaster loss severity. This paper proposes a hybrid learning model to improve disaster event classification and damage severity identification. The model combines image and text data, using ResNet50 to extract features from images, and using long short-term memory with an attention mechanism to learn sequences from text. This combination allows for a more contextual and informative representation of the input data. The experimental results shows that the proposed multimodal approach achieves significantly better results in disaster event classification attaining an accuracy of 90.31%, compared to existing methods. Furthermore, the model demonstrates promising capabilities in assessing damage severity, offering significant improvements for disaster management and response preparation where accuracy and dependability are crucial.
“Leveraging Multimodal Deep Learning For Natural Disaster Event Classification And Its Damage Severity Analysis Through Social Media Posts” Metadata:
- Title: ➤ Leveraging Multimodal Deep Learning For Natural Disaster Event Classification And Its Damage Severity Analysis Through Social Media Posts
- Author: ➤ Nivedita Kasturi, Shashikumar Guruputra Totad, Goldina Ghosh
- Language: English
“Leveraging Multimodal Deep Learning For Natural Disaster Event Classification And Its Damage Severity Analysis Through Social Media Posts” Subjects and Themes:
- Subjects: Damage severity identification - Disaster event classification - Hybrid deep learning - Multi-modality analytics - Social media posts
Edition Identifiers:
- Internet Archive ID: 101-24433
Downloads Information:
The book is available for download in "texts" format, the size of the file-s is: 12.04 Mbs, the file-s for this book were downloaded 13 times, the file-s went public at Fri Dec 06 2024.
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1Wonders of the Jungle
By Sarath Kumar Ghosh

How do elephants drink? What is the Law of the Jungle at the water hole? How does an elephant baby learn to feed and learn to swim? How do they walk under water? In what order do buffaloes drink? How do buffaloes fight the tiger? These and other wild inhabitants of the Indian jungle such as pigs, wild dogs, deer, camels, bears and birds are discussed in lively stories to entertain but mainly educate children of school age. "One of the great thinkers of the world has said that all the sciences are embodied in natural history. Hence natural history should be taught to a child from an early age. Perhaps the best method of teaching it is to set forth the characteristics of animals in the form of a narrative. Then the child reads the narrative with pleasure and almost as a story, not as a tedious "lesson." In this book the animals are described in their daily life, and the main scientific facts and principles concerning each animal are woven into the narrative as a part of that daily life." (Summary by Phil Chenevert and from the Preface)
“Wonders of the Jungle” Metadata:
- Title: Wonders of the Jungle
- Author: Sarath Kumar Ghosh
- Language: English
- Publish Date: 1915
Edition Specifications:
- Format: Audio
- Number of Sections: 16
- Total Time: 3:33:36
Edition Identifiers:
- libriVox ID: 7311
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- File Name: wondersofthejungle_1304_librivox
- File Format: zip
- Total Time: 3:33:36
- Download Link: Download link
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