Choosing how to encode a real-world problem as a machine learning task i...
Localizing desired objects from remote sensing images is of great use in...
The Visual Question Answering (VQA) system offers a user-friendly interf...
Aiming at answering questions based on the content of remotely sensed im...
Unmanned aerial vehicles (UAVs) are widely applied for purposes of
inspe...
Unmanned aerial vehicles (UAVs) are now widely applied to data acquisiti...
In deep learning research, self-supervised learning (SSL) has received g...
Deep learning has proven to be a very effective approach for Hyperspectr...
Visual question answering (VQA) for remote sensing scene has great poten...
The Earth's surface is continually changing, and identifying changes pla...
Building height retrieval from synthetic aperture radar (SAR) imagery is...
Most publicly available datasets for image classification are with singl...
Semantic change detection (SCD) extends the change detection (CD) task t...
Many current deep learning approaches make extensive use of backbone net...
Clouds are a very important factor in the availability of optical remote...
Aerial scene recognition is a fundamental research problem in interpreti...
Band selection refers to the process of choosing the most relevant bands...
Deep learning-based coastline detection algorithms have begun to outshin...
Training Convolutional Neural Networks (CNNs) for very high resolution i...
Object retrieval and reconstruction from very high resolution (VHR) synt...
Deep learning in remote sensing has become an international hype, but it...
Building segmentation is of great importance in the task of remote sensi...
Aerial scene recognition is a fundamental task in remote sensing and has...
Aerial scene recognition is a fundamental task in remote sensing and has...
Visual crowd counting has been recently studied as a way to enable peopl...
Along with the increasing use of unmanned aerial vehicles (UAVs), large
...
Access to labeled reference data is one of the grand challenges in super...
Multi-label classification plays a momentous role in perceiving intricat...
Most current semantic segmentation approaches fall back on deep convolut...
Most current semantic segmentation approaches fall back on deep convolut...
Vehicle detection is a significant and challenging task in aerial remote...
Aerial image classification is of great significance in remote sensing
c...
Object detection and semantic segmentation are two main themes in object...
Semantic segmentation in high resolution remote sensing images is a
fund...
Change detection is one of the central problems in earth observation and...
In this paper we tackle a very novel problem, namely height estimation f...
In this letter, we propose a pseudo-siamese convolutional neural network...
Standing at the paradigm shift towards data-intensive science, machine
l...