A review of building detection from very high resolution optical remote sensing images
Building detection from very high resolution (VHR) optical remote sensing images, which is
an essential but challenging task in remote sensing, has attracted increased attention in …
an essential but challenging task in remote sensing, has attracted increased attention in …
A full-level fused cross-task transfer learning method for building change detection using noise-robust pretrained networks on crowdsourced labels
Accurate building change detection is crucial for understanding urban development.
Although fully supervised deep learning-based methods for building change detection have …
Although fully supervised deep learning-based methods for building change detection have …
A Review of Building Extraction from Remote Sensing Imagery: Geometrical Structures and Semantic Attributes
In the remote sensing community, extracting buildings from remote sensing imagery has
triggered great interest. While many studies have been conducted, a comprehensive review …
triggered great interest. While many studies have been conducted, a comprehensive review …
Generative reasoning integrated label noise robust deep image representation learning
The development of deep learning based image representation learning (IRL) methods has
attracted great attention for various image understanding problems. Most of these methods …
attracted great attention for various image understanding problems. Most of these methods …
IUNet-IF: identification of construction waste using unmanned aerial vehicle remote sensing and multi-layer deep learning methods
Considering current problems in the identifying, locating, and supervising of construction
waste, it is difficult to achieve real-time target judgement and identification in the short term …
waste, it is difficult to achieve real-time target judgement and identification in the short term …
Multitype label noise modeling and uncertainty-weighted label correction for concealed object detection
C Wang, J Shi, C Tao, FL Xu, X Tang… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Recently, plenty of millimeter-wave image concealed object detection models have
achieved superior performance on benchmark datasets. The success of these models …
achieved superior performance on benchmark datasets. The success of these models …
AIO2: Online Correction of Object Labels for Deep Learning with Incomplete Annotation in Remote Sensing Image Segmentation
While the volume of remote sensing (RS) data is increasing daily, deep learning in Earth
observation (EO) faces lack of accurate annotations for supervised optimization …
observation (EO) faces lack of accurate annotations for supervised optimization …
Multimodal Co-Learning Meets Remote Sensing: Taxonomy, State of the Art, and Future Works
In remote sensing (RS), multiple modalities of data are usually available, eg, RGB,
multispectral, hyperspectral, light detection and ranging (LiDAR), and synthetic aperture …
multispectral, hyperspectral, light detection and ranging (LiDAR), and synthetic aperture …
Label noise robust image representation learning based on supervised variational autoencoders in remote sensing
Due to the publicly available thematic maps and crowd-sourced data, remote sensing (RS)
image annotations can be gathered at zero cost for training deep neural networks (DNNs) …
image annotations can be gathered at zero cost for training deep neural networks (DNNs) …
[PDF][PDF] Deep image representation learning for knowledge discovery from earth observation data archives
G Sümbül - 2023 - depositonce.tu-berlin.de
Advances in remote sensing (RS) technology have increased the availability of images
regularly acquired by satelliteborne and airborne sensors, while free data policies support …
regularly acquired by satelliteborne and airborne sensors, while free data policies support …