Artificial neural network approaches for disaster management: A literature review
Disaster management (DM) is one of the leading fields that deal with the humanitarian
aspects of emergencies. The field has attracted researchers because of its ever-increasing …
aspects of emergencies. The field has attracted researchers because of its ever-increasing …
Industry 4.0-oriented deep learning models for human activity recognition
According to the Industry 4.0 vision, humans in a smart factory, should be equipped with
formidable and seamless communication capabilities and integrated into a cyber-physical …
formidable and seamless communication capabilities and integrated into a cyber-physical …
[HTML][HTML] Recognition of human activity using GRU deep learning algorithm
S Mohsen - Multimedia Tools and Applications, 2023 - Springer
Human activity recognition (HAR) is a challenging issue in several fields, such as medical
diagnosis. Recent advances in the accuracy of deep learning have contributed to solving the …
diagnosis. Recent advances in the accuracy of deep learning have contributed to solving the …
An automated earthquake classification model based on a new butterfly pattern using seismic signals
Background Seismic signals are useful for earthquake detection and classification.
Therefore, various artificial intelligence (AI) models have been used with seismic signals to …
Therefore, various artificial intelligence (AI) models have been used with seismic signals to …
EEG-based human emotion prediction using an LSTM model
S Mohsen, AG Alharbi - 2021 IEEE international midwest …, 2021 - ieeexplore.ieee.org
It is deemed essential to identify and classify human emotions via deep learning with
computers. Therefore, electroencephalogram (EEG) is extensively used as a physiological …
computers. Therefore, electroencephalogram (EEG) is extensively used as a physiological …
ConvEQ: Convolutional neural network for earthquake phase classification using short time frequency transform
We present C onv EQ as a tool for discriminating seismic phases, leveraging artificial
intelligence technique (Convolutional Neural Network) for short-time Frequency Transform …
intelligence technique (Convolutional Neural Network) for short-time Frequency Transform …
[HTML][HTML] 3D convolution recurrent neural networks for multi-Label earthquake magnitude classification
We examine a classification task in which signals of naturally occurring earthquakes are
categorized ranging from minor to major, based on their magnitude. Generalized to a single …
categorized ranging from minor to major, based on their magnitude. Generalized to a single …
A General Purpose Neural Architecture for Geospatial Systems
Geospatial Information Systems are used by researchers and Humanitarian Assistance and
Disaster Response (HADR) practitioners to support a wide variety of important applications …
Disaster Response (HADR) practitioners to support a wide variety of important applications …
An Earthquake Alert system using Internet of Things
NV Teja, SP Akshay, KA Khaleed… - 2024 10th …, 2024 - ieeexplore.ieee.org
This project introduces an innovative earthquake detection system leveraging
accelerometers for seismic sensing. By incorporating accelerometers from widely available …
accelerometers for seismic sensing. By incorporating accelerometers from widely available …
A comparative analysis of machine learning and grey models
G He, KM Ahmad, W Yu, X Xu, J Kumar - arXiv preprint arXiv:2104.00871, 2021 - arxiv.org
Artificial Intelligence (AI) has recently shown its capabilities for almost every field of life.
Machine Learning, which is a subset of AI, is aHOT'topic for researchers. Machine Learning …
Machine Learning, which is a subset of AI, is aHOT'topic for researchers. Machine Learning …