Naonori Ueda 研究室

主宰者：Naonori Ueda

理化学研究所・RIKEN Center for Advanced Intelligence Project

AI 要約（直近 5 年の研究成果）

本研究室は、衛星画像やドローン、地震観測データなどの地球規模の観測データを処理・解析し、自然災害や地球表面の変化を検出・予測する研究に取り組んでいます。山火事の焼跡検出、建物被害の抽出、水深推定、地すべりリスク評価など、リモートセンシング技術を活用した様々な応用課題に対して、機械学習やディープラーニング手法を用いた自動解析システムを開発しています。これらのシステムでは、単に予測精度を高めるだけでなく、なぜそのような結果に至ったかを説明可能にすることを重視しています。画像認識モデルの内部動作を可視化する手法や、予測に寄与する要因を特定する手法を導入し、ブラックボックス化しやすい深層学習の判断根拠を明らかにする取り組みを行っています。加えて、地震による地殻変形の物理シミュレーション、台風の強度予測、交通ナビゲーション、建物や土地被覆の分類など、多様な時空間データを対象とした予測・最適化の問題に取り組んでいます。物理法則を機械学習に組み込む方法や、計算の効率化、大規模データの処理高速化など、実用的で堅牢なシステムの構築を目指した研究を展開しています。

※ AI（Claude）が、公開されている論文要旨から研究の問い・手法・主要な発見を事実情報として抽出・再構成して自動生成しています。誤りを含む可能性があるため、正確性は研究室公式情報でご確認ください。

外部リンク

研究成果（54 件）

[2026] A Spatiotemporal Evaluation Framework for MODIS-Derived Fire Events
DOI: https://doi.org/10.5194/isprs-annals-xi-3-2026-151-2026
[2025] Multi-horizon prediction of tropical cyclone intensity and its interpretability with temporal fusion transformer
DOI: https://doi.org/10.1038/s41598-025-15522-7
[2025] Landslide susceptibility mapping based on data mining models in Lesser Caucasus and Kura foreland basin (Armenia and Azerbaijan)
DOI: https://doi.org/10.1080/19475705.2025.2537221
[2025] Study on the Evaluation of Optimal Remote Sensing Features for Bushfire
DOI: https://doi.org/10.1109/igarss55030.2025.11242352
[2025] SHapley Additive exPlanations (SHAP) for Landslide Susceptibility Models: Shedding Light on Explainable AI
DOI: https://doi.org/10.5194/isprs-annals-x-g-2025-81-2025
[2025] Evaluation of Key Remote Sensing Features for Bushfire Analysis
DOI: https://doi.org/10.3390/rs17111823
[2025] Searching Optimum Route With Variable Travel Time
DOI: https://doi.org/10.1109/access.2025.3529027
[2024] Fault geometry invariance and dislocation potential in antiplane crustal deformation: physics-informed simultaneous solutions
DOI: https://doi.org/10.1186/s40645-024-00654-7
[2024] Multi-class AUC maximization for imbalanced ordinal multi-stage tropical cyclone intensity change forecast
DOI: https://doi.org/10.1016/j.mlwa.2024.100569
[2024] Using active cooling/heating for 1C1R grey-box model parameter identification in an actual environment: A proof-of-concept study
DOI: https://doi.org/10.1177/01436244241252258

続きを表示（残り 44 件）

[2024] Improving the Efficiency of Training Physics-Informed Neural Networks Using Active Learning
DOI: https://doi.org/10.1007/s00354-024-00253-6
[2024] INTERPRETABLE DEEP INPAINTING BASED ON SUBSURFACE STRUCTURE DATA FOR SPATIAL INTERPOLATION OF SEISMIC MOTIONS
DOI: https://doi.org/10.5610/jaee.24.5_35
[2023] Efficient Network Representation Learning via Cluster Similarity
DOI: https://doi.org/10.1007/s41019-023-00222-x
[2023] Moving Object Detection by Low-Rank Analysis of Region-Based Correlated Motion Fields
DOI: https://doi.org/10.1109/igarss52108.2023.10282752
[2023] Water depth estimation from Sentinel-2 imagery using advanced machine learning methods and explainable artificial intelligence
DOI: https://doi.org/10.1080/19475705.2023.2225691
[2023] Centrality measure and visualization technique for multiple-parent nodes of earthquakes based on correlation-metric
DOI: https://doi.org/10.1007/s41109-023-00541-y
[2023] Comment on ‘Geophysical inversion and optimal transport’ by M. Sambridge, A. Jackson and A. P. Valentine
DOI: https://doi.org/10.1093/gji/ggad001
[2022] On the use of XAI for CNN Model Interpretation: A Remote Sensing Case Study
DOI: https://doi.org/10.1109/csde56538.2022.10089337
[2022] MSBDA-Net: Multi-scale Siamese Building Damage Assessment Network
DOI: https://doi.org/10.1109/csde56538.2022.10089353
[2022] Fast Binary Network Hashing via Graph Clustering
DOI: https://doi.org/10.1109/bigdata55660.2022.10021047
[2022] Unboxing the Black Box of Attention Mechanisms in Remote Sensing Big Data Using XAI
DOI: https://doi.org/10.3390/rs14246254
[2022] Physics-informed deep learning approach for modeling crustal deformation
DOI: https://doi.org/10.1038/s41467-022-34922-1
[2022] Scalable Finite-Element Viscoelastic Crustal Deformation Analysis Accelerated with Data-Driven Method
DOI: https://doi.org/10.1109/scalah56622.2022.00008
[2022] Application and Potential of Drone Technology in Oil Palm Plantation: Potential and Limitations
DOI: https://doi.org/10.1155/2022/5385505
[2022] A Deep Learning Approach for Automated Building Outlines Extraction in Compact Urban Environments
DOI: https://doi.org/10.1109/igarss46834.2022.9884697
[2022] Deep Ensemble Learning for Land Cover Classification Based on Hyperspectral Prisma Image
DOI: https://doi.org/10.1109/igarss46834.2022.9884203
[2022] Deep-learning real/bogus classification for the Tomo-e Gozen transient survey
DOI: https://doi.org/10.1093/pasj/psac047
[2022] Earthquake-Induced Ground Deformation Assessment via Sentinel-1 Radar Aided at Darbandikhan Town
DOI: https://doi.org/10.1155/2022/2020069
[2022] BDD-Net: An End-to-End Multiscale Residual CNN for Earthquake-Induced Building Damage Detection
DOI: https://doi.org/10.3390/rs14092214
[2022] Performance Evaluation of Hospital Site Suitability Using Multilayer Perceptron (MLP) and Analytical Hierarchy Process (AHP) Models in Malacca, Malaysia
DOI: https://doi.org/10.3390/su14073731
[2022] Fusion of the Multisource Datasets for Flood Extent Mapping Based on Ensemble Convolutional Neural Network (CNN) Model
DOI: https://doi.org/10.1155/2022/2887502
[2022] Fire-Net: A Deep Learning Framework for Active Forest Fire Detection
DOI: https://doi.org/10.1155/2022/8044390
[2022] 152K-computer-node parallel scalable implicit solver for dynamic nonlinear earthquake simulation
DOI: https://doi.org/10.1145/3492805.3492814
[2022] Concise Parameter Identification Method for 1C1R Gray-Box Model Using Thermal Balance Points Associated with Active Cooling/Heating
DOI: https://doi.org/10.1016/j.ifacol.2022.11.226
[2022] Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data
DOI: https://doi.org/10.52202/068431-1512
[2021] Loss function based second-order Jensen inequality and its application to particle variational inference
[2021] Automated Building Detection from Airborne LiDAR and Very High-Resolution Aerial Imagery with Deep Neural Network
DOI: https://doi.org/10.3390/rs13234803
[2021] Fast and Accurate Anchor Graph-based Label Prediction
DOI: https://doi.org/10.1145/3459637.3482258
[2021] Spatio-temporal clustering of earthquakes based on distribution of magnitudes
DOI: https://doi.org/10.1007/s41109-021-00413-3
[2021] Deep Mixture Point Processes
DOI: https://doi.org/10.1527/tjsai.36-5_c-l37
[2021] Evaluation of PM2.5 Particulate Matter and Noise Pollution in Tikrit University Based on GIS and Statistical Modeling
DOI: https://doi.org/10.3390/su13179571
[2021] Accelerated Diffusion-Based Sampling by the Non-Reversible Dynamics with Skew-Symmetric Matrices
DOI: https://doi.org/10.3390/e23080993
[2021] Monotonic Neural Network for Ground-Motion Predictions to Avoid Overfitting to Recorded Sites
DOI: https://doi.org/10.1785/0220210099
[2021] Development of UAV-Based PM2.5 Monitoring System
DOI: https://doi.org/10.3390/drones5030060
[2021] The Effect of War on Land Use Dynamics in Mosul Iraq Using Remote Sensing and GIS Techniques
DOI: https://doi.org/10.1109/igarss47720.2021.9553165
[2021] Deep Neural Network Utilizing Remote Sensing Datasets for Flood Hazard Susceptibility Mapping in Brisbane, Australia
DOI: https://doi.org/10.3390/rs13132638
[2021] Fast scalable implicit solver with convergence of equation-based modeling and data-driven learning
DOI: https://doi.org/10.1145/3468267.3470616
[2021] Simulation of broad-band ground motions with consistent long-period and short-period components using the Wasserstein interpolation of acceleration envelopes
DOI: https://doi.org/10.1093/gji/ggab225
[2021] Ground-Motion Prediction Model Based on Neural Networks to Extract Site Properties from Observational Records
DOI: https://doi.org/10.1785/0120200339
[2021] Fast Similarity Computation for t-SNE
DOI: https://doi.org/10.1109/icde51399.2021.00149
[2021] Fast algorithm for anchor graph hashing
DOI: https://doi.org/10.14778/3447689.3447696
[2021] Predicting PM<sub>2.5</sub> levels over the north of Iraq using regression analysis and geographical information system (GIS) techniques
DOI: https://doi.org/10.1080/19475705.2021.1946602
[2021] Application of an Ensemble Statistical Approach in Spatial Predictions of Bushfire Probability and Risk Mapping
DOI: https://doi.org/10.1155/2021/6638241
[2021] Geospatial Multicriteria Analysis for Earthquake Risk Assessment: Case Study of Fujairah City in the UAE
DOI: https://doi.org/10.1155/2021/6638316

科研費（0 件）

まだデータがありません（KAKEN 取り込み後に表示）。

所属学会・役職（0 件）

まだデータがありません（学会データ連携後に表示）。

AI 要約（直近 5 年の研究成果）

外部リンク

関連研究室(8 件)

研究成果（54 件）

科研費（0 件）

所属学会・役職（0 件）