[HTML][HTML] Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review
EH Houssein, A Hammad, AA Ali - Neural Computing and Applications, 2022 - Springer
Affective computing, a subcategory of artificial intelligence, detects, processes, interprets,
and mimics human emotions. Thanks to the continued advancement of portable non …
and mimics human emotions. Thanks to the continued advancement of portable non …
Emotion recognition using multi-modal data and machine learning techniques: A tutorial and review
In recent years, the rapid advances in machine learning (ML) and information fusion has
made it possible to endow machines/computers with the ability of emotion understanding …
made it possible to endow machines/computers with the ability of emotion understanding …
Spatio-temporal feature encoding for traffic accident detection in VANET environment
Z Zhou, X Dong, Z Li, K Yu, C Ding… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In the Vehicular Ad hoc Networks (VANET) environment, recognizing traffic accident events
in the driving videos captured by vehicle-mounted cameras is an essential task. Generally …
in the driving videos captured by vehicle-mounted cameras is an essential task. Generally …
Non-iterative and fast deep learning: Multilayer extreme learning machines
In the past decade, deep learning techniques have powered many aspects of our daily life,
and drawn ever-increasing research interests. However, conventional deep learning …
and drawn ever-increasing research interests. However, conventional deep learning …
Visual–tactile fusion for object recognition
The camera provides rich visual information regarding objects and becomes one of the most
mainstream sensors in the automation community. However, it is often difficult to be …
mainstream sensors in the automation community. However, it is often difficult to be …
Deep learning-based model predictive control for continuous stirred-tank reactor system
A continuous stirred-tank reactor (CSTR) system is widely applied in wastewater treatment
processes. Its control is a challenging industrial-process-control problem due to great …
processes. Its control is a challenging industrial-process-control problem due to great …
[PDF][PDF] 极限学习机前沿进展与趋势
徐睿， 梁循， 齐金山， 李志宇， 张树森 - 计算机学报, 2019 - cjc.ict.ac.cn
摘要极限学习机(ExtremeLearningMachine, ELM) 作为前馈神经网络学习中一种全新的训练
框架, 在行为识别, 情感识别和故障诊断等方面被广泛应用, 引起了各个领域的高度关注和深入 …
框架, 在行为识别, 情感识别和故障诊断等方面被广泛应用, 引起了各个领域的高度关注和深入 …
Mixture correntropy for robust learning
Correntropy is a local similarity measure defined in kernel space, hence can combat large
outliers in robust signal processing and machine learning. So far, many robust learning …
outliers in robust signal processing and machine learning. So far, many robust learning …
Faster-YOLO: An accurate and faster object detection method
Y Yin, H Li, W Fu - Digital Signal Processing, 2020 - Elsevier
In the computer vision, object detection has always been considered one of the most
challenging issues because it requires classifying and locating objects in the same scene …
challenging issues because it requires classifying and locating objects in the same scene …
EEG-based emotion recognition using hierarchical network with subnetwork nodes
Emotions play a crucial role in decision-making, brain activity, human cognition, and social
intercourse. This paper proposes a hierarchical network structure with subnetwork nodes to …
intercourse. This paper proposes a hierarchical network structure with subnetwork nodes to …