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Real-time GeoAI for high-resolution mapping and segmentation of arctic permafrost features

https://doi.org/10.1145/3557918.3565869
0 signed · 27 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-0-387-39940-9_482openalex-snapshot
Average Precision
inferredcites →https://doi.org/10.1038/nature14338openalex-snapshot
Climate change and the permafrost carbon feedback
inferredcites →https://doi.org/10.1088/1748-9326/11/4/040201openalex-snapshot
Changing permafrost in a warming world and feedbacks to the Earth system
inferredcites →https://doi.org/10.1109/access.2018.2877890openalex-snapshot
Benchmark Analysis of Representative Deep Neural Network Architectures
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.106openalex-snapshot
Feature Pyramid Networks for Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.660openalex-snapshot
Pyramid Scene Parsing Network
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00439openalex-snapshot
Sparse Instance Activation for Real-Time Instance Segmentation
inferredcites →https://doi.org/10.1109/iccv.2017.322openalex-snapshot
Mask R-CNN
inferredcites →https://doi.org/10.1109/iccv.2019.00615openalex-snapshot
Scale-Aware Trident Networks for Object Detection
inferredcites →https://doi.org/10.1109/iccv.2019.00925openalex-snapshot
YOLACT: Real-Time Instance Segmentation
inferredcites →https://doi.org/10.14358/pers.21-00059r2openalex-snapshot
An Optimal GeoAI Workflow for Pan-Arctic Permafrost Feature Detection from High-Resolution Satellite Imagery
inferredcites →https://doi.org/10.3390/ijgi11070385openalex-snapshot
GeoAI for Large-Scale Image Analysis and Machine Vision: Recent Progress of Artificial Intelligence in Geography
inferredcites →https://doi.org/10.3390/jimaging6120137openalex-snapshot
Use of Very High Spatial Resolution Commercial Satellite Imagery and Deep Learning to Automatically Map Ice-Wedge Polygons across Tundra Vegetation Types
inferredcites →https://doi.org/10.3390/rs11020114openalex-snapshot
A Patch-Based Light Convolutional Neural Network for Land-Cover Mapping Using Landsat-8 Images
inferredcites →https://doi.org/10.3390/rs14122747openalex-snapshot
Accuracy, Efficiency, and Transferability of a Deep Learning Model for Mapping Retrogressive Thaw Slumps across the Canadian Arctic
inferredcites →https://doi.org/10.5194/egusphere-egu2020-15481openalex-snapshot
Deep learning for monthly Arctic sea ice concentration prediction
inferredcites →https://doi.org/10.5311/josis.2020.20.658openalex-snapshot
GeoAI: Where machine learning and big data converge in GIScience

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4762408openalex-extracted
A Multi-Scale Vision Transformer-Based Multimodal Geoai Model for Mapping Arctic Permafrost Thaw
inferred← citeshttps://doi.org/10.1080/13658816.2023.2191256openalex-snapshot
Explainable GeoAI: can saliency maps help interpret artificial intelligence’s learning process? An empirical study on natural feature detection
inferred← citeshttps://doi.org/10.1080/13658816.2024.2397441openalex-snapshot
Geospatial foundation models for image analysis: evaluating and enhancing NASA-IBM Prithvi’s domain adaptability
inferred← citeshttps://doi.org/10.1109/igarss53475.2024.10642540openalex-snapshot
Undercovereisagenten - Integrating Low-Cost UAVS and Community Insights for Enhanced Permafrost Monitoring
inferred← citeshttps://doi.org/10.1109/jstars.2025.3564310openalex-snapshot
A Multiscale Vision Transformer-Based Multimodal GeoAI Model for Mapping Arctic Permafrost Thaw
inferred← citeshttps://doi.org/10.1145/3615886.3627747openalex-snapshot
Assessment of a new GeoAI foundation model for flood inundation mapping
inferred← citeshttps://doi.org/10.2139/ssrn.4897692openalex-snapshot
Evaluation of Explainable Ai Models in Analysis of Transferable Features of Geothermal Indicators
inferred← citeshttps://doi.org/10.3390/rs16050797openalex-snapshot
Segment Anything Model Can Not Segment Anything: Assessing AI Foundation Model’s Generalizability in Permafrost Mapping
inferred← citeshttps://doi.org/10.3390/rs18091421openalex-snapshot
Evaluation of the Potential of Very-High-Resolution Satellite Imagery in Large-Scale Mapping
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