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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 …
A survey of deep learning-based object detection methods and datasets for overhead imagery
Significant advancements and progress made in recent computer vision research enable
more effective processing of various objects in high-resolution overhead imagery obtained …
more effective processing of various objects in high-resolution overhead imagery obtained …
Few-shot object detection on remote sensing images
In this article, we deal with the problem of object detection on remote sensing images.
Previous researchers have developed numerous deep convolutional neural network (CNN) …
Previous researchers have developed numerous deep convolutional neural network (CNN) …
An ensemble architecture of deep convolutional Segnet and Unet networks for building semantic segmentation from high-resolution aerial images
Building objects is one of the principal features that are essential for updating the geospatial
database. Extracting building features from high-resolution imagery automatically and …
database. Extracting building features from high-resolution imagery automatically and …
Predicting ground-level scene layout from aerial imagery
We introduce a novel strategy for learning to extract semantically meaningful features from
aerial imagery. Instead of manually labeling the aerial imagery, we propose to predict …
aerial imagery. Instead of manually labeling the aerial imagery, we propose to predict …
Hybrid dilated convolution guided feature filtering and enhancement strategy for hyperspectral image classification
With the increasing maturity of optics and photonics, hyperspectral technology has also
greatly advanced. Hyperspectral images composed of hundreds of adjacent bands and …
greatly advanced. Hyperspectral images composed of hundreds of adjacent bands and …
Detecting moving shadows: algorithms and evaluation
Moving shadows need careful consideration in the development of robust dynamic scene
analysis systems. Moving shadow detection is critical for accurate object detection in video …
analysis systems. Moving shadow detection is critical for accurate object detection in video …
Using dynamic programming for solving variational problems in vision
Dynamic programming is discussed as an approach to solving variational problems in
vision. Dynamic programming ensures global optimality of the solution, is numerically stable …
vision. Dynamic programming ensures global optimality of the solution, is numerically stable …
Semantic segmentation of satellite images using deep-unet
The ability to extract roads, detect buildings, and identify land cover types from satellite
images is critical for sustainable development, agriculture, forestry, urban planning, and …
images is critical for sustainable development, agriculture, forestry, urban planning, and …
Automated detection of buildings from single VHR multispectral images using shadow information and graph cuts
In this study, we propose a novel methodology for automated detection of buildings from
single very-high-resolution (VHR) multispectral images. The methodology uses the principal …
single very-high-resolution (VHR) multispectral images. The methodology uses the principal …