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 …
An integrated parallel inner deep learning models information fusion with Bayesian optimization for land scene classification in satellite images
Classification of remote scenes in satellite imagery has many applications, such as
surveillance, earth observation, etc. Classifying high-resolution remote sensing images in …
surveillance, earth observation, etc. Classifying high-resolution remote sensing images in …
ResRandSVM: Hybrid approach for acute lymphocytic leukemia classification in blood smear images
Acute Lymphocytic Leukemia is a type of cancer that occurs when abnormal white blood
cells are produced in the bone marrow which do not function properly, crowding out healthy …
cells are produced in the bone marrow which do not function properly, crowding out healthy …
Evaluation of deep learning models for building damage map** in emergency response settings
Integrated with remote sensing technology, deep learning has been increasingly used for
rapid damage assessment. Despite reportedly having high accuracy, the approach requires …
rapid damage assessment. Despite reportedly having high accuracy, the approach requires …
Deep Learning Models for Hazard-Damaged Building Detection Using Remote Sensing Datasets: A Comprehensive Review
Building collapse is a leading cause of casualties and economic losses during disasters.
Accurate and timely assessment of building damage is critical for effective emergency …
Accurate and timely assessment of building damage is critical for effective emergency …
Deep Learning in Big Data, Image, and Signal Processing in the Modern Digital Age
Data, such as images and signals, are constantly generated from various industries,
including the internet [1, 2]. As a result, new technologies have surfaced to track the origin of …
including the internet [1, 2]. As a result, new technologies have surfaced to track the origin of …
[HTML][HTML] Advanced hybrid CNN-Bi-LSTM model augmented with GA and FFO for enhanced cyclone intensity forecasting
Predicting cyclone intensity is an important aspect of weather forecasting since it influences
disaster preparation and response. This framework addresses the pressing need for precise …
disaster preparation and response. This framework addresses the pressing need for precise …
Traffic monitoring system design considering multi-hazard disaster risks
Roadways are critical infrastructure in our society, providing services for people through and
between cities. However, they are prone to closures and disruptions, especially after …
between cities. However, they are prone to closures and disruptions, especially after …
Bridging satellite missions: deep transfer learning for enhanced tropical cyclone intensity estimation
Geostationary satellites are valuable tools for monitoring the entire lifetime of tropical
cyclones (TCs). Although the most widely used method for TC intensity estimation is manual …
cyclones (TCs). Although the most widely used method for TC intensity estimation is manual …
A Novel Transfer Learning based CNN Model for Wildfire Susceptibility Prediction
Wildfires are one of the most commonly occurring natural disasters in the world, posing
significant threats to ecosystems and human settlements alike. One of the most important …
significant threats to ecosystems and human settlements alike. One of the most important …