Automated detection and forecasting of covid-19 using deep learning techniques: A review
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
[HTML][HTML] Visual saliency-based landslide identification using super-resolution remote sensing data
S Sreelakshmi, SSV Chandra - Results in Engineering, 2024 - Elsevier
Landslides, ubiquitous geological hazards on steep slopes, present formidable challenges
in tropical regions with dense rainforest vegetation, impeding accurate mapping and risk …
in tropical regions with dense rainforest vegetation, impeding accurate mapping and risk …
Deep-Sentiment: An Effective Deep Sentiment Analysis Using a Decision-Based Recurrent Neural Network (D-RNN)
P Durga, D Godavarthi - IEEE Access, 2023 - ieeexplore.ieee.org
Sentiment analysis is a sub-domain in opinion mining that extracts sentiments from the
users' opinions from text messages. Opinions from E-commerce websites, blogs, online …
users' opinions from text messages. Opinions from E-commerce websites, blogs, online …
[HTML][HTML] Optimized gravitational search algorithm for feature fusion in a multimodal biometric system
In recent years, multimodal biometric systems have gained significant attention due to their
capacity to enhance recognition accuracy and robustness. The integration of multiple …
capacity to enhance recognition accuracy and robustness. The integration of multiple …
[HTML][HTML] Internet of Things with Deep Learning Techniques for Pandemic Detection: A Comprehensive Review of Current Trends and Open Issues
Technological advancements for diverse aspects of life have been made possible by the
swift development and application of Internet of Things (IoT) based technologies. IoT …
swift development and application of Internet of Things (IoT) based technologies. IoT …
Secure Your Steps: A Class-Based Ensemble Framework for Real-Time Fall Detection Using Deep Neural Networks
Falls represent a significant public health concern, particularly concerning vulnerable
populations such as older adults. Accurate detection and classification of falls are critical for …
populations such as older adults. Accurate detection and classification of falls are critical for …
Efficient deep learning models for predicting super-utilizers in smart hospitals
In healthcare, a huge amount is paid to meet the requirements of High-Need High-Cost
(HNHC) patients, also known as super-utilizers. The major aim of the proposed study is to …
(HNHC) patients, also known as super-utilizers. The major aim of the proposed study is to …
Autonomous artificial intelligence systems for fraud detection and forensics in dark web environments
Artificial Intelligence (AI) influenced technical aspects of research for generating automated
intelligent behaviors covering divergent domains but has shown appreciable results when …
intelligent behaviors covering divergent domains but has shown appreciable results when …
[PDF][PDF] A framework for robust attack detection and classification using rap-densenet
Network attacks must be effectively identified and categorized to guarantee strong security.
However, current techniques frequently have trouble correctly identifying and categorizing …
However, current techniques frequently have trouble correctly identifying and categorizing …
Ensuring intrusion detection for iot services through an improved CNN
Abstract Internet of Things (IoT) devices are challenging to manage information security due
to some factors such as processing capability, exponential growth in homes, and their low …
to some factors such as processing capability, exponential growth in homes, and their low …