A survey on object detection in optical remote sensing images
Object detection in optical remote sensing images, being a fundamental but challenging
problem in the field of aerial and satellite image analysis, plays an important role for a wide …
problem in the field of aerial and satellite image analysis, plays an important role for a wide …
Machine learning for uav-aided its: A review with comparative study
Unmanned Aerial Vehicles (UAVs) have immense potential to enhance Intelligent Transport
Systems (ITS) by aiding in real-time traffic monitoring, emergency response, and …
Systems (ITS) by aiding in real-time traffic monitoring, emergency response, and …
Learning rotation-invariant convolutional neural networks for object detection in VHR optical remote sensing images
Object detection in very high resolution optical remote sensing images is a fundamental
problem faced for remote sensing image analysis. Due to the advances of powerful feature …
problem faced for remote sensing image analysis. Due to the advances of powerful feature …
Multi-class geospatial object detection and geographic image classification based on collection of part detectors
The rapid development of remote sensing technology has facilitated us the acquisition of
remote sensing images with higher and higher spatial resolution, but how to automatically …
remote sensing images with higher and higher spatial resolution, but how to automatically …
[BOOK][B] Computer vision using local binary patterns
The recent emergence of Local Binary Patterns (LBP) has led to significant progress in
applying texture methods to various computer vision problems and applications. The focus …
applying texture methods to various computer vision problems and applications. The focus …
Vehicle detection in satellite images by hybrid deep convolutional neural networks
Detecting small objects such as vehicles in satellite images is a difficult problem. Many
features (such as histogram of oriented gradient, local binary pattern, scale-invariant feature …
features (such as histogram of oriented gradient, local binary pattern, scale-invariant feature …
Hierarchical and robust convolutional neural network for very high-resolution remote sensing object detection
Object detection is a basic issue of very high-resolution remote sensing images (RSIs) for
automatically labeling objects. At present, deep learning has gradually gained the …
automatically labeling objects. At present, deep learning has gradually gained the …
Orientation robust object detection in aerial images using deep convolutional neural network
Detecting objects in aerial images is challenged by variance of object colors, aspect ratios,
cluttered backgrounds, and in particular, undetermined orientations. In this paper, we …
cluttered backgrounds, and in particular, undetermined orientations. In this paper, we …
ORSIm detector: A novel object detection framework in optical remote sensing imagery using spatial-frequency channel features
With the rapid development of spaceborne imaging techniques, object detection in optical
remote sensing imagery has drawn much attention in recent decades. While many …
remote sensing imagery has drawn much attention in recent decades. While many …
Fuzzy-aided solution for out-of-view challenge in visual tracking under IoT-assisted complex environment
With the rapid development in computer vision domain, research on object tracking has
directed more attention by scholars. Out of view (OV) is an important challenge often …
directed more attention by scholars. Out of view (OV) is an important challenge often …