Continual deep learning for time series modeling
The multi-layer structures of Deep Learning facilitate the processing of higher-level
abstractions from data, thus leading to improved generalization and widespread …
abstractions from data, thus leading to improved generalization and widespread …
Deep-net: A lightweight CNN-based speech emotion recognition system using deep frequency features
Artificial intelligence (AI) and machine learning (ML) are employed to make systems smarter.
Today, the speech emotion recognition (SER) system evaluates the emotional state of the …
Today, the speech emotion recognition (SER) system evaluates the emotional state of the …
A Human–Computer Interaction framework for emotion recognition through time-series thermal video sequences
Abstract Infrared-Thermal Imaging is a non-contact mechanism for psychophysiological
research and application in Human–Computer Interaction (HCI). Real-time detection of the …
research and application in Human–Computer Interaction (HCI). Real-time detection of the …
Deep feature extraction and classification of android malware images
The Android operating system has gained popularity and evolved rapidly since the previous
decade. Traditional approaches such as static and dynamic malware identification …
decade. Traditional approaches such as static and dynamic malware identification …
[Retracted] Efficient Algorithms for E‐Healthcare to Solve Multiobject Fuse Detection Problem
I Ahmad, I Ullah, WU Khan… - Journal of …, 2021 - Wiley Online Library
Object detection plays a vital role in the fields of computer vision, machine learning, and
artificial intelligence applications (such as FUSE‐AI (E‐healthcare MRI scan), face detection …
artificial intelligence applications (such as FUSE‐AI (E‐healthcare MRI scan), face detection …
Freeway accident detection and classification based on the multi-vehicle trajectory data and deep learning model
D Yang, Y Wu, F Sun, J Chen, D Zhai, C Fu - Transportation research part …, 2021 - Elsevier
The freeway accident detection and classification have attracted much attention of
researchers in the past decades. With the popularity of Global Navigation Satellite System …
researchers in the past decades. With the popularity of Global Navigation Satellite System …
Contrast enhancement of fundus images by employing modified PSO for improving the performance of deep learning models
Computer-Aided diagnosis (CAD) is a widely used technique to detect and diagnose
diseases like tumors, cancers, edemas, etc. Several critical retinal diseases like diabetic …
diseases like tumors, cancers, edemas, etc. Several critical retinal diseases like diabetic …
Digital twin model: A real-time emotion recognition system for personalized healthcare
Emotion recognition (ER) in healthcare has drawn substantial attention owing to recent
advancements in machine-learning (ML) and deep-learning (DL) techniques. The ER …
advancements in machine-learning (ML) and deep-learning (DL) techniques. The ER …
1D-CNN: Speech Emotion Recognition System Using a Stacked Network with Dilated CNN Features.
S Kwon - Computers, Materials & Continua, 2021 - search.ebscohost.com
Emotion recognition from speech data is an active and emerging area of research that plays
an important role in numerous applications, such as robotics, virtual reality, behavior …
an important role in numerous applications, such as robotics, virtual reality, behavior …
A matrix determinant feature extraction approach for decoding motor and mental imagery EEG in subject-specific tasks
This study introduces a novel matrix determinant feature extraction approach for efficient
classification of motor and mental imagery activities from electroencephalography (EEG) …
classification of motor and mental imagery activities from electroencephalography (EEG) …