Historical maps classification has become an important application in today's scenario of
everchanging land boundaries. Historical map changes include the change in boundaries of …

The effectiveness of learning-based point cloud upsampling pipelines heavily relies on the
upsampling modules and feature extractors used therein. For the point upsampling module …

We explore the application of super-resolution techniques to satellite imagery, and the
effects of these techniques on object detection algorithm performance. Specifically, we …

Segmentation and classification are two imperative, yet challenging tasks in image analysis
for remote-sensing applications. In the former, an image is divided into spatially continuous …

As a new type of network, the types of attack in the Internet of Vehicles (IoV) are constantly
emerging and changing. Consequently, the machine learning based intrusion detection …

During the construction process, many construction vehicles gather in a small area in a short
period, thus the accurate identification of dense multiple vehicles is of great significance for …

The satellite imaging system allows easy and effective remote collection of large amounts of
information about the objects of interest from even inaccessible areas for a long time …

The paper reviews the vehicle detection methods using the intrusive and non-intrusive
sensors. The objective of literature review is to summarize the sensors and technologies …

In digital era, being stranded from very basic telecommunication protocols and internet
makes vehicle rerouting-like crucial tools more difficult or even impossible, especially in …

Hyperspectral image analysis has been gaining research attention thanks to the current
advances in sensor design which have made acquiring such imagery much more affordable …