Automatic Target Detection from Satellite Imagery Using Machine Learning [PDF]
Sensors, 2022 Object detection is a vital step in satellite imagery-based computer vision applications such as precision agriculture, urban planning and defense applications.
Arsalan Tahir +6 more
doaj +3 more sources
The Potential of Satellite Imagery for Surveying Whales [PDF]
Sensors, 2021 The emergence of very high-resolution (VHR) satellite imagery (less than 1 m spatial resolution) is creating new opportunities within the fields of ecology and conservation biology. The advancement of sub-meter resolution imagery has provided greater confidence in the detection and identification of features on the ground, broadening the realm of ...
Hannah C Cubaynes +2 more
exaly +6 more sources
Gray whale detection in satellite imagery using deep learning
Remote Sensing in Ecology and Conservation, 2023 The combination of very high resolution (VHR) satellite remote sensing imagery and deep learning via convolutional neural networks provides opportunities to improve global whale population surveys through increasing efficiency and spatial coverage.
Katherine M. Green +9 more
doaj +2 more sources
A cloud detection algorithm for satellite imagery based on deep learning
Remote Sensing of Environment, 2019 Reliable detection of clouds is a critical pre-processing step in optical satellite based remote sensing. Currently, most methods are based on classifying invidual pixels from their spectral signatures, therefore they do not incorporate the spatial ...
Jacob Høxbroe Jeppesen +2 more
exaly +2 more sources
Satellite imagery in use [PDF]
Forced Migration Review, 2008 Satellite imagery is becoming an increasingly important toolfor the humanitarian community.
Einar Bjorgo +3 more
doaj +1 more source
SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery [PDF]
Neural Information Processing Systems, 2022 Unsupervised pre-training methods for large vision models have shown to enhance performance on downstream supervised tasks. Developing similar techniques for satellite imagery presents significant opportunities as unlabelled data is plentiful and the ...
Yezhen Cong +8 more
semanticscholar +1 more source
Combining OpenStreetMap with Satellite Imagery to Enhance Cross-View Geo-Localization [PDF]
SensorsCross-view geo-localization (CVGL) aims to determine the capture location of street-view images by matching them with corresponding 2D maps, such as satellite imagery. While recent bird’s eye view (BEV)-based methods have advanced this task by addressing
Yuekun Hu, Yingfan Liu, Bin Hui
doaj +2 more sources
The Outcome of the 2022 Landslide4Sense Competition: Advanced Landslide Detection From Multisource Satellite Imagery [PDF]
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 The scientific outcomes of the 2022 Landslide4Sense (L4S) competition organized by the Institute of Advanced Research in Artificial Intelligence are presented here.
O. Ghorbanzadeh +14 more
semanticscholar +1 more source
Open High-Resolution Satellite Imagery: The WorldStrat Dataset - With Application to Super-Resolution [PDF]
Neural Information Processing Systems, 2022 Analyzing the planet at scale with satellite imagery and machine learning is a dream that has been constantly hindered by the cost of difficult-to-access highly-representative high-resolution imagery.
Julien Cornebise +2 more
semanticscholar +1 more source
Global mining footprint mapped from high-resolution satellite imagery
Communications Earth & Environment, 2023 Mining is of major economic, environmental and societal consequence, yet knowledge and understanding of its global footprint is still limited. Here, we produce a global mining land use dataset via remote sensing analysis of high-resolution, publicly ...
L. Tang, Tim T. Werner
semanticscholar +1 more source