Deep learning-based semantic segmentation of urban features in satellite images: A review and meta-analysis
Availability of very high-resolution remote sensing images and advancement of deep
learning methods have shifted the paradigm of image classification from pixel-based and …
learning methods have shifted the paradigm of image classification from pixel-based and …
Challenges and opportunities in remote sensing-based crop monitoring: A review
Building a more resilient food system for sustainable development and reducing uncertainty
in global food markets both require concurrent and near-real-time and reliable crop …
in global food markets both require concurrent and near-real-time and reliable crop …
Cross-city matters: A multimodal remote sensing benchmark dataset for cross-city semantic segmentation using high-resolution domain adaptation networks
Artificial intelligence (AI) approaches nowadays have gained remarkable success in single-
modality-dominated remote sensing (RS) applications, especially with an emphasis on …
modality-dominated remote sensing (RS) applications, especially with an emphasis on …
Landslide susceptibility map** using multiscale sampling strategy and convolutional neural network: A case study in Jiuzhaigou region
Landslides are one of the most widespread natural disasters and pose severe threats to
people, properties, and the environment in many areas. Landslide susceptibility map** …
people, properties, and the environment in many areas. Landslide susceptibility map** …
Large-scale individual building extraction from open-source satellite imagery via super-resolution-based instance segmentation approach
Building footprint is a primary dataset of an urban geographic information system (GIS)
database. Therefore, it is essential to establish a robust and automated framework for large …
database. Therefore, it is essential to establish a robust and automated framework for large …
Building extraction from remote sensing images with sparse token transformers
Deep learning methods have achieved considerable progress in remote sensing image
building extraction. Most building extraction methods are based on Convolutional Neural …
building extraction. Most building extraction methods are based on Convolutional Neural …
Deep learning segmentation and classification for urban village using a worldview satellite image based on U-Net
Z Pan, J Xu, Y Guo, Y Hu, G Wang - Remote Sensing, 2020 - mdpi.com
Unplanned urban settlements exist worldwide. The geospatial information of these areas is
critical for urban management and reconstruction planning but usually unavailable …
critical for urban management and reconstruction planning but usually unavailable …
DR-Net: An improved network for building extraction from high resolution remote sensing image
M Chen, J Wu, L Liu, W Zhao, F Tian, Q Shen, B Zhao… - Remote Sensing, 2021 - mdpi.com
At present, convolutional neural networks (CNN) have been widely used in building
extraction from remote sensing imagery (RSI), but there are still some bottlenecks. On the …
extraction from remote sensing imagery (RSI), but there are still some bottlenecks. On the …