Deep learning models are widely being employed for object detection due to their high
performance. However, the majority of applications that require object detection are …

Multispectral image pairs can provide the combined information, making object detection
applications more reliable and robust in the open world. To fully exploit the different …

Cross-modality fusing complementary information of multispectral remote sensing image
pairs can improve the perception ability of detection algorithms, making them more robust …

Multi-scale target detection in synthetic aperture radar (SAR) images is one of the key
techniques of SAR image interpretation, which is widely used in national defense and …

CubeSats provide a low-cost, convenient, and effective way of acquiring remote sensing
data, and have great potential for remote sensing object detection. Although deep learning …

Difficult object detection and class imbalance in object detection are the two main
challenges faced by aerial image object detection. Difficult objects include small objects …

Remote sensor image object detection is an important technology for Earth observation, and
is used in various tasks such as forest fire monitoring and ocean monitoring. Image object …

AIM To propose an algorithm for automatic detection of diabetic retinopathy (DR) lesions
based on ultra-widefield scanning laser ophthalmoscopy (SLO). METHODS The algorithm …

In SAR images, there are objects with large scale difference, which is called cross-scale
objects. For example, there are both large-scale airport objects and small-scale ship objects …

The problem under consideration is the blurring of aerial images of the Earth, which reduces
the quality of object detection during remote sensing. The purpose of this study is to improve …