The development of self-driving cars increases driving safety and accelerates urban
transportation. These systems must have robust and real-time understanding of traffic …

In this paper, we propose a novel fully unsupervised framework that learns action
representations suitable for the action segmentation task from the single input video itself …

In order to reduce the overuse of herbicides, an automatic spraying system can be utilized,
assisted with machine vision-based techniques to accurately target weeds. In this paper, a …

In this paper, a method is presented for Multi-Object Tracking (MOT) in presence of partial or
complete occlusions. This work focuses on improved object detection and data association …

Active contour models (ACMs) are popular and widely used for many image segmentation
applications and obtain promising results. However, these methods are unable to achieve …

Object tracking has always been one of the most challenging topics in machine vision. In
recent years, trackers have used RGB-T datasets to overcome the limitations of single …

This paper aimed to evaluate the effectiveness of subset selection of markers for genome-
enabled prediction of genetic values using radial basis function neural networks (RBFNN) …

A wrist‐based photoplethysmography (PPG) tool offers a simple and non‐invasive approach
for applications in vital sign monitoring and healthcare. However, in a telecare network …

In video surveillance, multiple objects tracking (MOT) is a challenging task due to object
matching problem in consecutive frames. The present paper aims to propose an improved …

Recent advances in remote sensing technology have led to the creation of many sensors
with very high spatial resolution, which enable researchers to detect and recognize earth …