Classification and detection of natural disasters using machine learning and deep learning techniques: A review
For efficient disaster management, it is essential to identify and categorize natural disasters.
The classical approaches and current technological advancements for identifying …
The classical approaches and current technological advancements for identifying …
Transforming ground disaster response: Recent technological advances, challenges, and future trends for rapid and accurate real-world applications of survivor …
Recent technological advancements, encompassing cutting-edge sensors, drones, and AI
systems, present novel prospects for enhancing survivor detection in disaster scenarios …
systems, present novel prospects for enhancing survivor detection in disaster scenarios …
A Hypersphere Information Granule-Based Fuzzy Classifier Embedded With Fuzzy Cognitive Maps for Classification of Imbalanced Data
R Yin, W Lu, J Yang - IEEE Transactions on Emerging Topics in …, 2023 - ieeexplore.ieee.org
In this article, a hypersphere information granule-based fuzzy classifier integrated with Fuzzy
Cognitive Maps (FCM), named FCM-IGFC, is proposed for the classification of imbalanced …
Cognitive Maps (FCM), named FCM-IGFC, is proposed for the classification of imbalanced …
[HTML][HTML] Deep artificial intelligence applications for natural disaster management systems: A methodological review
Deep learning techniques through semantic segmentation networks have been widely used
for natural disaster analysis and response. The underlying base of these implementations …
for natural disaster analysis and response. The underlying base of these implementations …
Enhancing natural disaster analysis and waste classification: a novel VGG-FL approach
S Soundararajan, R Josphineleela, AK Bisht… - Environmental …, 2024 - Springer
The study of natural disasters is a crucial field that involves analyzing the occurrence,
impact, and aftermath of various natural hazards that can cause significant harm to …
impact, and aftermath of various natural hazards that can cause significant harm to …
Challenges in data-based geospatial modeling for environmental research and practice
With the rise of electronic data, particularly Earth observation data, data-based geospatial
modelling using machine learning (ML) has gained popularity in environmental research …
modelling using machine learning (ML) has gained popularity in environmental research …
Image-Based Natural Disaster Classification with Deep Learning: A Comparative Analysis
SE Alamsyah, SF Djamhari, SH Sudjono… - … on Industry 4.0 …, 2024 - ieeexplore.ieee.org
Natural disasters, including earthquakes, cyclones, floods, and wildfires, cause significant
environmental damage and have emerged as a major global issue. These events can result …
environmental damage and have emerged as a major global issue. These events can result …
A Novel Active Learning Approach to Label One Million Unknown Malware Variants
A Bensaoud, J Kalita - Available at SSRN 4884050 - papers.ssrn.com
Active learning seeks to reduce the cost of labeling samples by finding unlabeled examples
about which the current model is least certain and sending them to an annotator/expert to …
about which the current model is least certain and sending them to an annotator/expert to …