Arrhythmia is a cardiac conduction disorder characterized by irregular heartbeats.
Abnormalities in the conduction system can manifest in the electrocardiographic (ECG) …

We propose an end-to-end place recognition model based on a novel deep neural network.
First, we propose to exploit the spatial pyramid structure of the images to enhance the vector …

With an overwhelming increase in the demand of autonomous systems, especially in the
applications related to intelligent robotics and visual surveillance, come stringent accuracy …

Background The electrocardiogram (ECG) has been widely used in the diagnosis of heart
disease such as arrhythmia due to its simplicity and non-invasive nature. Arrhythmia can be …

Image registration is an important technique in many computer vision applications such as
image fusion, image retrieval, object tracking, face recognition, change detection and so on …

Clinical depression is a neurological disorder that can be identified by analyzing the
Electroencephalography (EEG) signals. However, the major drawback in using EEG to …

Scene recognition is challenging due to the complicated spatial arrangement and varied
object distribution inside the scene images. Deep learning methods, especially …

Prototype-based approaches generally provide better explainability and are widely used for
classification. However, the majority of them suffer from system obesity and lack …

Pioneering the traditional fuzzy rule-based (FRB) systems, deep rule-based (DRB)
classifiers are able to offer both human-level performance and transparent system structure …

An extended model of multilayer perceptron (MLP) based on reduced geometric algebra
(RGA), namely RGA-MLP, is proposed for multi-dimensional signal processing. The RGA …