Robust vehicle detection in low-resolution aerial imagery

2010 ◽  
Author(s):  
Samir Sahli ◽  
Yueh Ouyang ◽  
Yunlong Sheng ◽  
Daniel A. Lavigne
Keyword(s):  
Vehicle Detection ◽  
Aerial Imagery ◽  
Low Resolution

scholarly journals Mapping the Unseen: Exploiting Super-Resolution for Semantic Segmentation in Low-Resolution Images

2020 ◽  
Author(s):  
Matheus B. Pereira ◽  
Jefersson Alex Dos Santos
Keyword(s):  
Remote Sensing ◽  
Pattern Recognition ◽  
Super Resolution ◽  
Remote Sensing Data ◽  
Semantic Segmentation ◽  
The Other ◽  
Aerial Imagery ◽  
Aerial Images ◽  
Remote Sensing Images ◽  
Low Resolution

High-resolution aerial images are usually not accessible or affordable. On the other hand, low-resolution remote sensing data is easily found in public open repositories. The problem is that the low-resolution representation can compromise pattern recognition algorithms, especially semantic segmentation. In this M.Sc. dissertation1 , we design two frameworks in order to evaluate the effectiveness of super-resolution in the semantic segmentation of low-resolution remote sensing images. We carried out an extensive set of experiments on different remote sensing datasets. The results show that super-resolution is effective to improve semantic segmentation performance on low-resolution aerial imagery, outperforming unsupervised interpolation and achieving semantic segmentation results comparable to highresolution data.

Height-adaptive vehicle detection in aerial imagery using metadata of EO sensor

2020 ◽  
Author(s):  
Seongjo Kim ◽  
Won Yeong Heo ◽  
HyunSeong Sung ◽  
DeukRyeol Yoon ◽  
Jongmin Jeong
Keyword(s):  
Vehicle Detection ◽  
Aerial Imagery

Vehicle detection from aerial imagery

2011 ◽  
Author(s):  
Joshua Gleason ◽  
Ara V. Nefian ◽  
Xavier Bouyssounousse ◽  
Terry Fong ◽  
George Bebis
Keyword(s):  
Vehicle Detection ◽  
Aerial Imagery
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