Understanding deep learning techniques for recognition of human emotions using facial expressions: A comprehensive survey
Emotion recognition plays a significant role in cognitive psychology research. However,
measuring emotions is a challenging task. Thus, several approaches have been designed …
measuring emotions is a challenging task. Thus, several approaches have been designed …
The deep learning applications in IoT-based bio-and medical informatics: a systematic literature review
Z Amiri, A Heidari, NJ Navimipour… - Neural Computing and …, 2024 - Springer
Nowadays, machine learning (ML) has attained a high level of achievement in many
contexts. Considering the significance of ML in medical and bioinformatics owing to its …
contexts. Considering the significance of ML in medical and bioinformatics owing to its …
A dual-channel dehaze-net for single image dehazing in visual Internet of Things using PYNQ-Z2 board
A large number of emerging applications, such as autonomous navigation, space
exploration, surveillance, military target detection, and remote sensing, use outdoor images …
exploration, surveillance, military target detection, and remote sensing, use outdoor images …
Benchmarks for machine learning in depression discrimination using electroencephalography signals
Diagnosis of depression using electroencephalography (EEG) is an emerging field of study.
When mental health facilities are unavailable, the use of EEG as an objective measure for …
When mental health facilities are unavailable, the use of EEG as an objective measure for …
Optimized Xception Learning Model and XgBoost Classifier for Detection of Multiclass Chest Disease from X-ray Images
Computed tomography (CT) scans, or radiographic images, were used to aid in the early
diagnosis of patients and detect normal and abnormal lung function in the human chest …
diagnosis of patients and detect normal and abnormal lung function in the human chest …
Multi-level training and testing of CNN models in diagnosing multi-center COVID-19 and pneumonia X-ray images
Featured Application Despite their reported high accuracy, a significant limitation of current
AI-assisted COVID-19 diagnostic models is that they are often trained on datasets sourced …
AI-assisted COVID-19 diagnostic models is that they are often trained on datasets sourced …
Entropy‐Based Emotion Recognition from Multichannel EEG Signals Using Artificial Neural Network
Humans experience a variety of emotions throughout the course of their daily lives, including
happiness, sadness, and rage. As a result, an effective emotion identification system is …
happiness, sadness, and rage. As a result, an effective emotion identification system is …
[PDF][PDF] Pandemic disease detection through wireless communication using infrared image based on deep learning
M Alhameed, F Jeribi, BME Elnaim… - Mathematical …, 2023 - researchgate.net
Rapid diagnosis to test diseases, such as COVID-19, is a significant issue. It is a routine
virus test in a reverse transcriptase-polymerase chain reaction. However, a test like this …
virus test in a reverse transcriptase-polymerase chain reaction. However, a test like this …
Detection of Diseases in Pandemic: A Predictive Approach Using Stack Ensembling on Multi-Modal Imaging Data
R Mansoor, MA Shah, HA Khattak, S Mussadiq… - Electronics, 2022 - mdpi.com
Deep Learning (DL) in Medical Imaging is an emerging technology for diagnosing various
diseases, ie, pneumonia, lung cancer, brain stroke, breast cancer, etc. In Machine Learning …
diseases, ie, pneumonia, lung cancer, brain stroke, breast cancer, etc. In Machine Learning …
[PDF][PDF] Comprehensive study: machine learning approaches for COVID-19 diagnosis
AN Hussein, SVAD Makki… - International Journal of …, 2023 - academia.edu
Coronavirus disease 2019 (COVID-19) is caused a large number of death since has
declared as an international pandemic in December 2019, and it is spreading all over the …
declared as an international pandemic in December 2019, and it is spreading all over the …