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20222026
most citedOn the Transferability of Learning Models for Semantic Segmentation for Remote Sensing Data

7 citations · 8 across the 4 of their papers we have counts for

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cs.CV2026

Olbedo: An Albedo and Shading Aerial Dataset for Large-Scale Outdoor Environments

Shuang Song, Debao Huang, Deyan Deng +4

Intrinsic image decomposition (IID) of outdoor scenes is crucial for relighting, editing, and understanding large-scale environments, but progress has been limited by the lack of r…

cs.CV2025

Synthetic Data Matters: Re-training with Geo-typical Synthetic Labels for Building Detection

Shuang Song, Yang Tang, Rongjun Qin

Deep learning has significantly advanced building segmentation in remote sensing, yet models struggle to generalize on data of diverse geographic regions due to variations in city…

cs.CV2024

Image Fusion in Remote Sensing: An Overview and Meta Analysis

Hessah Albanwan, Rongjun Qin, Yang Tang

Image fusion in Remote Sensing (RS) has been a consistent demand due to its ability to turn raw images of different resolutions, sources, and modalities into accurate, complete, an…

cs.CV20237 cited

On the Transferability of Learning Models for Semantic Segmentation for Remote Sensing Data

Rongjun Qin, Guixiang Zhang, Yang Tang

Recent deep learning-based methods outperform traditional learning methods on remote sensing (RS) semantic segmentation/classification tasks. However, they require large training d…

cs.CV20221 cited

Sat2lod2: A Software For Automated Lod-2 Modeling From Satellite-Derived Orthophoto And Digital Surface Model

Shengxi Gui, Rongjun Qin, Yang Tang

Deriving LoD2 models from orthophoto and digital surface models (DSM) reconstructed from satellite images is a challenging task. Existing solutions are mostly system approaches tha…