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Emotion recognition from unimodal to multimodal analysis: A review
The omnipresence of numerous information sources in our daily life brings up new
alternatives for emotion recognition in several domains including e-health, e-learning …
alternatives for emotion recognition in several domains including e-health, e-learning …
[HTML][HTML] Facial emotion recognition using conventional machine learning and deep learning methods: current achievements, analysis and remaining challenges
AR Khan - Information, 2022 - mdpi.com
Facial emotion recognition (FER) is an emerging and significant research area in the pattern
recognition domain. In daily life, the role of non-verbal communication is significant, and in …
recognition domain. In daily life, the role of non-verbal communication is significant, and in …
[HTML][HTML] Breast cancer classification from ultrasound images using probability-based optimal deep learning feature fusion
After lung cancer, breast cancer is the second leading cause of death in women. If breast
cancer is detected early, mortality rates in women can be reduced. Because manual breast …
cancer is detected early, mortality rates in women can be reduced. Because manual breast …
Application of deep learning techniques in diagnosis of covid-19 (coronavirus): a systematic review
Covid-19 is now one of the most incredibly intense and severe illnesses of the twentieth
century. Covid-19 has already endangered the lives of millions of people worldwide due to …
century. Covid-19 has already endangered the lives of millions of people worldwide due to …
Brain tumor segmentation using K‐means clustering and deep learning with synthetic data augmentation for classification
Image processing plays a major role in neurologists' clinical diagnosis in the medical field.
Several types of imagery are used for diagnostics, tumor segmentation, and classification …
Several types of imagery are used for diagnostics, tumor segmentation, and classification …
[HTML][HTML] COVID-19 case recognition from chest CT images by deep learning, entropy-controlled firefly optimization, and parallel feature fusion
In healthcare, a multitude of data is collected from medical sensors and devices, such as X-
ray machines, magnetic resonance imaging, computed tomography (CT), and so on, that …
ray machines, magnetic resonance imaging, computed tomography (CT), and so on, that …
Cloud computing-based framework for breast cancer diagnosis using extreme learning machine
Globally, breast cancer is one of the most significant causes of death among women. Early
detection accompanied by prompt treatment can reduce the risk of death due to breast …
detection accompanied by prompt treatment can reduce the risk of death due to breast …
[HTML][HTML] Utilizing CNN-LSTM techniques for the enhancement of medical systems
COVID-19 is one of the most chronic and serious infections of recent years due to its
worldwide spread. Determining who was genuinely affected when the disease spreads …
worldwide spread. Determining who was genuinely affected when the disease spreads …
Detection of COVID-19 in smartphone-based breathing recordings: A pre-screening deep learning tool
This study was sought to investigate the feasibility of using smartphone-based breathing
sounds within a deep learning framework to discriminate between COVID-19, including …
sounds within a deep learning framework to discriminate between COVID-19, including …
Classification of citrus plant diseases using deep transfer learning
MZU Rehman, F Ahmed, MA Khan, U Tariq, SS Jamal… - 2021 - qspace.qu.edu.qa
In recent years, the field of deep learning has played an important role towards automatic
detection and classification of diseases in vegetables and fruits. This in turn has helped in …
detection and classification of diseases in vegetables and fruits. This in turn has helped in …