In recent years, deep learning (DL), a rebranding of neural networks (NNs), has risen to the
top in numerous areas, namely computer vision (CV), speech recognition, and natural …

Recent years have seen a significant amount of transportation data collected from multiple
sources including road sensors, probe, GPS, CCTV and incident reports. Similar to many …

Object detection, as a fundamental task in computer vision, has been developed
enormously, but is still challenging work, especially for Unmanned Aerial Vehicle (UAV) …

Abstract “Unmanned aerial vehicles”(UAVs) are now being used for a wide range of
surveillance applications. Specifically, the detection of on-ground vehicles from UAV images …

Vehicle detection is one of the important applications of object detection in intelligent
transportation systems. It aims to extract specific vehicle-type information from pictures or …

Vehicle detection in aerial images is a crucial image processing step for many applications
like screening of large areas. In recent years, several deep learning based frameworks have …

In recent years, object detection became more and more important following the successful
results from studies in deep learning. Two types of neural network architectures are used for …

The detection of true loop closure in Visual Simultaneous Localization And Mapping
(vSLAM) can help in many ways, it helps in re-localization, improves the accuracy of the …

Object detection and classification is important for video surveillance applications. Counting
vehicles like cars, truck and vans is useful for intelligent transportation systems to identify …

Crop leaf purpling is a common phenotypic change when plants are subject to some biotic
and abiotic stresses during their growth. The extraction of purple leaves can monitor crop …