Automated emotion recognition: Current trends and future perspectives
Background Human emotions greatly affect the actions of a person. The automated emotion
recognition has applications in multiple domains such as health care, e-learning …
recognition has applications in multiple domains such as health care, e-learning …
Speech emotion recognition approaches: A systematic review
A Hashem, M Arif, M Alghamdi - Speech Communication, 2023 - Elsevier
The speech emotion recognition (SER) field has been active since it became a crucial
feature in advanced Human-Computer Interaction (HCI), and wide real-life applications use …
feature in advanced Human-Computer Interaction (HCI), and wide real-life applications use …
Occupancy prediction using deep learning approaches across multiple space types: A minimum sensing strategy
The proliferation of sensing technologies has allowed the collection of occupancy-related
data to support various building applications, including adaptive HVAC and lighting controls …
data to support various building applications, including adaptive HVAC and lighting controls …
Robust speech emotion recognition using CNN+ LSTM based on stochastic fractal search optimization algorithm
One of the main challenges facing the current approaches of speech emotion recognition is
the lack of a dataset large enough to train the currently available deep learning models …
the lack of a dataset large enough to train the currently available deep learning models …
[HTML][HTML] Multimodal emotion recognition on RAVDESS dataset using transfer learning
Emotion Recognition is attracting the attention of the research community due to the multiple
areas where it can be applied, such as in healthcare or in road safety systems. In this paper …
areas where it can be applied, such as in healthcare or in road safety systems. In this paper …
Improving brain tumor classification performance with an effective approach based on new deep learning model named 3ACL from 3D MRI data
Many machine learning-based studies have been carried out in the literature for the
detection of brain tumors using MRI data and most of what has been done in the last 6 years …
detection of brain tumors using MRI data and most of what has been done in the last 6 years …
[HTML][HTML] A proposal for multimodal emotion recognition using aural transformers and action units on ravdess dataset
Emotion recognition is attracting the attention of the research community due to its multiple
applications in different fields, such as medicine or autonomous driving. In this paper, we …
applications in different fields, such as medicine or autonomous driving. In this paper, we …
[HTML][HTML] Speech emotion recognition based on multiple acoustic features and deep convolutional neural network
K Bhangale, M Kothandaraman - Electronics, 2023 - mdpi.com
Speech emotion recognition (SER) plays a vital role in human–machine interaction. A large
number of SER schemes have been anticipated over the last decade. However, the …
number of SER schemes have been anticipated over the last decade. However, the …
Prediction model of drinking water source quality with potential industrial-agricultural pollution based on CNN-GRU-Attention
P Mei, M Li, Q Zhang, G Li - Journal of Hydrology, 2022 - Elsevier
It is of great significance for the operation and management of waterworks to accurately
predict the raw water quality. In this study, the turbidity and CODcr of raw water with light …
predict the raw water quality. In this study, the turbidity and CODcr of raw water with light …
Automated steel surface defect detection and classification using a new deep learning-based approach
In this study, a new deep learning-based approach has been developed that detects and
classifies surface defects that occur in the steel production process. The proposed …
classifies surface defects that occur in the steel production process. The proposed …