{"total":31,"rows":[{"id":"2103.00208","title":"Remote Sensing Image Change Detection with Transformers","created":"2021-02-27","cited_by_count":306,"area":null},{"id":"2402.01444","title":"Mission Critical -- Satellite Data is a Distinct Modality in Machine Learning","created":"2024-02-02","cited_by_count":77,"area":null},{"id":"2207.13159","title":"TINYCD: A (Not So) Deep Learning Model For Change Detection","created":"2022-07-26","cited_by_count":36,"area":null},{"id":"2201.04236","title":"Incidents1M: a large-scale dataset of images with natural disasters, damage, and incidents","created":"2022-01-11","cited_by_count":26,"area":null},{"id":"2105.07364","title":"BDANet: Multiscale Convolutional Neural Network with Cross-directional Attention for Building Damage Assessment from Satellite Images","created":"2021-05-16","cited_by_count":19,"area":null},{"id":"2205.13769","title":"Semantic-aware Dense Representation Learning for Remote Sensing Image Change Detection","created":"2022-05-27","cited_by_count":16,"area":null},{"id":"2212.01287","title":"SARAS-Net: Scale and Relation Aware Siamese Network for Change Detection","created":"2022-12-02","cited_by_count":13,"area":null},{"id":"2305.14722","title":"Continuous Cross-resolution Remote Sensing Image Change Detection","created":"2023-05-24","cited_by_count":8,"area":null},{"id":"2509.15788","title":"FoBa: A Foreground-Background co-Guided Method and New Benchmark for Remote Sensing Semantic Change Detection","created":"2025-09-19","cited_by_count":6,"area":null},{"id":"2307.10853","title":"Exploring Effective Priors and Efficient Models for Weakly-Supervised Change Detection","created":"2023-07-20","cited_by_count":5,"area":null},{"id":"2405.04800","title":"DeepDamageNet: A two-step deep-learning model for multi-disaster building damage segmentation and classification using satellite imagery","created":"2024-05-08","cited_by_count":5,"area":null},{"id":"2201.10389","title":"BLDNet: A Semi-supervised Change Detection Building Damage Framework using Graph Convolutional Networks and Urban Domain Knowledge","created":"2022-01-25","cited_by_count":4,"area":null},{"id":"2307.15128","title":"End-to-end Remote Sensing Change Detection of Unregistered Bi-temporal Images for Natural Disasters","created":"2023-07-27","cited_by_count":4,"area":null},{"id":"2405.13779","title":"Robust Disaster Assessment from Aerial Imagery Using Text-to-Image Synthetic Data","created":"2024-05-22","cited_by_count":4,"area":null},{"id":"2312.01576","title":"Learning Efficient Unsupervised Satellite Image-based Building Damage Detection","created":"2023-12-04","cited_by_count":3,"area":null},{"id":"2406.02506","title":"An Open-Source Tool for Mapping War Destruction at Scale in Ukraine using Sentinel-1 Time Series","created":"2024-06-04","cited_by_count":3,"area":null},{"id":"2107.04983","title":"Leveraging Domain Adaptation for Low-Resource Geospatial Machine Learning","created":"2021-07-11","cited_by_count":2,"area":null},{"id":"2111.02586","title":"Building Damage Mapping with Self-PositiveUnlabeled Learning","created":"2021-11-04","cited_by_count":2,"area":null},{"id":"2111.03693","title":"Disaster mapping from satellites: damage detection with crowdsourced point labels","created":"2021-11-05","cited_by_count":2,"area":null},{"id":"2201.10395","title":"Towards Cross-Disaster Building Damage Assessment with Graph Convolutional Networks","created":"2022-01-25","cited_by_count":2,"area":null},{"id":"2405.17734","title":"Towards Efficient Disaster Response via Cost-effective Unbiased Class Rate Estimation through Neyman Allocation Stratified Sampling Active Learning","created":"2024-05-28","cited_by_count":2,"area":null},{"id":"2409.15021","title":"Cross Branch Feature Fusion Decoder for Consistency Regularization-based Semi-Supervised Change Detection","created":"2024-09-23","cited_by_count":2,"area":null},{"id":"2206.09242","title":"GaLeNet: Multimodal Learning for Disaster Prediction, Management and Relief","created":"2022-06-18","cited_by_count":1,"area":null},{"id":"2208.03419","title":"Multi-view deep learning for reliable post-disaster damage classification","created":"2022-08-06","cited_by_count":1,"area":null},{"id":"2503.07911","title":"Visual and Text Prompt Segmentation: A Novel Multi-Model Framework for Remote Sensing","created":"2025-03-10","cited_by_count":1,"area":null},{"id":"2511.05461","title":"The Potential of Copernicus Satellites for Disaster Response: Retrieving Building Damage from Sentinel-1 and Sentinel-2","created":"2025-11-07","cited_by_count":1,"area":null},{"id":"2201.10523","title":"Interpretability in Convolutional Neural Networks for Building Damage Classification in Satellite Imagery","created":"2022-01-24","cited_by_count":0,"area":null},{"id":"2404.18235","title":"Flood Data Analysis on SpaceNet 8 Using Apache Sedona","created":"2024-04-28","cited_by_count":0,"area":null},{"id":"2411.18880","title":"GTPC-SSCD: Gate-guided Two-level Perturbation Consistency-based Semi-Supervised Change Detection","created":"2024-11-28","cited_by_count":0,"area":null},{"id":"2507.01547","title":"AI and Remote Sensing for Resilient and Sustainable Built Environments: A Review of Current Methods, Open Data and Future Directions","created":"2025-07-02","cited_by_count":0,"area":null},{"id":"2605.26381","title":"Multi-Modal Building Inspection via Perceiver IO Fusion of Satellite and Street-Level Imagery","created":"2026-05-25","cited_by_count":0,"area":null}],"next_cursor":null}