[HTML][HTML] Deep learning for land use and land cover classification based on hyperspectral and multispectral earth observation data: A review
Lately, with deep learning outpacing the other machine learning techniques in classifying
images, we have witnessed a growing interest of the remote sensing community in …
images, we have witnessed a growing interest of the remote sensing community in …
OpenStreetMap: Challenges and opportunities in machine learning and remote sensing
OpenStreetMap (OSM) is a community-based, freely available, editable map service created
as an alternative to authoritative sources. Given that it is edited mainly by volunteers with …
as an alternative to authoritative sources. Given that it is edited mainly by volunteers with …
SinoLC-1: The first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data
In China, the demand for a more precise perception of the national land surface has become
most urgent given the pace of development and urbanization. Constructing a very-high …
most urgent given the pace of development and urbanization. Constructing a very-high …
Representation-enhanced status replay network for multisource remote-sensing image classification
Deep-learning-based methods are widely used in multisource remote-sensing image
classification, and the improvement in their performance confirms the effectiveness of deep …
classification, and the improvement in their performance confirms the effectiveness of deep …
LANet: Local attention embedding to improve the semantic segmentation of remote sensing images
The trade-off between feature representation power and spatial localization accuracy is
crucial for the dense classification/semantic segmentation of remote sensing images (RSIs) …
crucial for the dense classification/semantic segmentation of remote sensing images (RSIs) …
Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks
In this work, we investigate various methods to deal with semantic labeling of very high
resolution multi-modal remote sensing data. Especially, we study how deep fully …
resolution multi-modal remote sensing data. Especially, we study how deep fully …
[HTML][HTML] X-ModalNet: A semi-supervised deep cross-modal network for classification of remote sensing data
D Hong, N Yokoya, GS **_A_case_study_of_Chinese_cities/links/6605ab86390c214cfd236f6f/Knowledge-guided-land-pattern-depiction-for-urban-land-use-map**-A-case-study-of-Chinese-cities.pdf" data-clk="hl=sr&sa=T&oi=gga&ct=gga&cd=9&d=13755045872882278609&ei=ULfGZ7uiJuehieoP9KefoQg" data-clk-atid="0eBZEli9474J" target="_blank">[PDF] researchgate.net
Knowledge-guided land pattern depiction for urban land use map**: A case study of Chinese cities
Accurate urban land-use maps, which reflect the complicated land-use pattern implied in the
function and distribution of land-cover types, play an important role in urban analysis. In …
function and distribution of land-cover types, play an important role in urban analysis. In …