Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …

Since the proposal of a fast learning algorithm for deep belief networks in 2006, the deep
learning techniques have drawn ever-increasing research interests because of their …

Image segmentation refers to the process of partitioning an image into mutually exclusive
regions. It can be considered as the most essential and crucial process for facilitating the …

Terrain geometry is, in general, nonsmooth, nonlinear, nonconvex, and, if perceived through
a robot-centric visual unit, appears partially occluded and noisy. This article presents the …

Abstract 3D imaging has a significant impact on many challenges in life sciences, because
biology is a 3-dimensional phenomenon. Current 3D imaging-technologies (various types …

Electrocardiogram (ECG) signal is a process that records the heart rate by using electrodes
and detects small electrical changes for each heat rate. It is used to investigate some types …

Stacked sparse denoising auto-encoders (SSDAs) have recently been shown to be
successful at removing noise from corrupted images. However, like most denoising …

Internet of Things (IoT) are vulnerable to both cyber and physical attacks. Therefore, a cyber-
physical security system against different kinds of attacks is in high demand. Traditionally …

Phase-shifting profilometry combined with Gray-code patterns projection has been widely
used for 3D measurement. In this technique, a phase-shifting algorithm is used to calculate …

We propose a bi-objective algorithm based on the k-nearest neighbors (biokNN) method to
perform imputation of missing values for data with multilevel structures with continuous …