Automatic identity recognition from ear images represents an active field of research within
the biometric community. The ability to capture ear images from a distance and in a covert …

Digital videos are now low-cost, easy to capture and easy to share on social media due to
the common feature of video recording in smart phones and digital devices. However, with …

In this paper, we investigate stable patterns of electroencephalogram (EEG) over time for
emotion recognition using a machine learning approach. Up to now, various findings of …

Emotion recognition from EEG signals has attracted much attention in affective computing.
Recently, a novel dynamic graph convolutional neural network (DGCNN) model was …

As a high-level function of the human brain, emotion is the external manifestation of people's
psychological characteristics. The emotion has a great impact on people's personality and …

Fuzzy clustering is a classical approach to provide the soft partition of data. Although its
enhancements have been intensively explored, fuzzy clustering still suffers from the …

With the direct input–output connections, a random vector functional link (RVFL) network is a
simple and effective learning algorithm for single-hidden layer feedforward neural networks …

Accurately and automatically recognizing the emotional states of human beings is the
central task in affective computing. The electroencephalography (EEG) data, generated from …

Broad learning system (BLS) has been proposed as an alternative method of deep learning.
The architecture of BLS is that the input is randomly mapped into series of feature spaces …

In modern manufacturing systems, a flexible job-shop schedule problem (FJSP) with random
machine breakdown has been widely studied. Two objectives, namely makespan and …