In this paper, we propose a probabilistic model for detecting relevant changes in registered
aerial image pairs taken with the time differences of several years and in different seasonal …

This monograph gives an introduction to the fundamentals of Markovian modeling in image
segmentation as well as a brief overview of recent advances in the field. Segmentation is …

In this paper, the problem of moving object detection in aerial video is addressed. While
motion cues have been extensively exploited in the literature, how to use spatial information …

In this paper, we give a comparative study on three Multilayer Markov Random Field (MRF)
based solutions proposed for change detection in optical remote sensing images, called …

In this paper, we introduce an automated Bayesian visual inspection framework for printed
circuit board (PCB) assemblies, which is able to simultaneously deal with various shaped …

Automated maritime object detection is a significant research challenge in intelligent marine
surveillance systems for the Internet of Things (IoT) and smart ocean applications. In …

In this paper, we address various challenges in multi-pedestrian and vehicle tracking in high-
resolution aerial imagery by intensive evaluation of a number of traditional and Deep …

Detection of moving objects by unmanned aerial vehicles (UAVs) is an important application
in the aerial transportation system. However, there are many problems to be handled such …

Robustly fitting a linear model from outlier-contaminated data is an important and basic task
in many scientific fields, and it is often tackled by consensus set maximization. There have …

In this paper, we present a new object-based hierarchical model for the joint probabilistic
extraction of vehicles and groups of corresponding vehicles-called traffic segments-in …