Exploring the Frontiers of Unsupervised Learning Techniques for Diagnosis of Cardiovascular Disorder: A Systematic Review
Accurate diagnosis and treatment of cardiovascular diseases require the integration of
cardiac imaging, which provides crucial information about the structure and function of the …
cardiac imaging, which provides crucial information about the structure and function of the …
A Comprehensive Overview of Transformative Potential of Machine Learning and Wireless Sensor Networks in Sustainable Urban Development
Wireless sensor networks (WSNs) have become essential elements in the advancement of
smart cities, enabling the collection and analysis of data in real time for a wide range of …
smart cities, enabling the collection and analysis of data in real time for a wide range of …
Light-FER: a lightweight facial emotion recognition system on edge devices
Facial emotion recognition (FER) systems are imperative in recent advanced artificial
intelligence (AI) applications to realize better human–computer interactions. Most deep …
intelligence (AI) applications to realize better human–computer interactions. Most deep …
A survey on deep learning algorithms in facial Emotion Detection and Recognition
PA Baffour, H Nunoo-Mensah… - Inform: Jurnal Ilmiah …, 2022 - ejournal.unitomo.ac.id
Facial emotion recognition (FER) forms part of affective computing, where computers are
trained to recognize human emotion from human expressions. Facial Emotion Recognition …
trained to recognize human emotion from human expressions. Facial Emotion Recognition …
Automatic detection of mental health status using alpha subband of EEG data
Electroencephalography (EEG) is an indispensable non-invasive analytical method in the
diagnosis and characterization of mental health. However, the conventional EEG …
diagnosis and characterization of mental health. However, the conventional EEG …
Automated alzheimer's disease diagnosis using norm features extracted from EEG signals
Alzheimer's disease (AD) is a neurodegenerative disorder that progresses over time and
affects cognitive abilities. It is marked by symptoms such as memory loss, language and …
affects cognitive abilities. It is marked by symptoms such as memory loss, language and …
Multiresolution feature fusion for smart diagnosis of schizophrenia in adolescents using EEG signals
Numerous studies on early detection of schizophrenia (SZ) have utilized all available
channels or employed set of a few time domain or frequency domain features, while a …
channels or employed set of a few time domain or frequency domain features, while a …
A machine learning framework for automatic diagnosis of schizophrenia using EEG signals
Schizophrenia (ScZ) is a chronic brain disorder that affects speech, mood, behaviour,
cognitive ability, etc. The people suffering from this disease often misinterpret reality, lose …
cognitive ability, etc. The people suffering from this disease often misinterpret reality, lose …
Multivariate EMG Signal Based Automated Hand Gestures Recognition Framework for Elder Care
Electromyogram (EMG) signals obtained from muscles can provide insights into the
biomechanics of human movement. EMG technology finds diverse applications including …
biomechanics of human movement. EMG technology finds diverse applications including …
Performance Comparison of Classification Models for Identification of Breast Lesions in Ultrasound Images
Globally, breast cancer is the most common disease among women. A region endures from
damage through any disease then the region is known as lesion. It is important to …
damage through any disease then the region is known as lesion. It is important to …