{"total":76,"rows":[{"id":"2207.08051","title":"SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery","created":"2022-07-17","cited_by_count":408,"area":null},{"id":"2107.07933","title":"Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks","created":"2021-07-16","cited_by_count":143,"area":null},{"id":"2304.14065","title":"Lightweight, Pre-trained Transformers for Remote Sensing Timeseries","created":"2023-04-27","cited_by_count":103,"area":null},{"id":"2302.02515","title":"Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey","created":"2023-02-06","cited_by_count":68,"area":null},{"id":"2301.04944","title":"ViTs for SITS: Vision Transformers for Satellite Image Time Series","created":"2023-01-12","cited_by_count":56,"area":null},{"id":"2205.01138","title":"Transformers in Time-series Analysis: A Tutorial","created":"2022-04-28","cited_by_count":46,"area":null},{"id":"2102.08820","title":"Crop mapping from image time series: deep learning with multi-scale label hierarchies","created":"2021-02-17","cited_by_count":42,"area":null},{"id":"2212.09840","title":"Dynamic Sparse Network for Time Series Classification: Learning What to \"see''","created":"2022-12-19","cited_by_count":22,"area":null},{"id":"2111.02682","title":"TimeMatch: Unsupervised Cross-Region Adaptation by Temporal Shift Estimation","created":"2021-11-04","cited_by_count":21,"area":null},{"id":"2204.00951","title":"A Sentinel-2 multi-year, multi-country benchmark dataset for crop classification and segmentation with deep learning","created":"2022-04-02","cited_by_count":19,"area":null},{"id":"2408.07314","title":"Kolmogorov-Arnold Networks (KAN) for Time Series Classification and Robust Analysis","created":"2024-08-14","cited_by_count":16,"area":null},{"id":"2203.09175","title":"Generalized Classification of Satellite Image Time Series with Thermal Positional Encoding","created":"2022-03-17","cited_by_count":14,"area":null},{"id":"2103.01695","title":"A Novel CNN-LSTM-based Approach to Predict Urban Expansion","created":"2021-03-02","cited_by_count":13,"area":null},{"id":"2404.03936","title":"Deep Learning for Satellite Image Time Series Analysis: A Review","created":"2024-04-05","cited_by_count":13,"area":null},{"id":"2103.15522","title":"Score-oriented loss (SOL) functions","created":"2021-03-29","cited_by_count":11,"area":null},{"id":"2104.04310","title":"Context-self contrastive pretraining for crop type semantic segmentation","created":"2021-04-09","cited_by_count":11,"area":null},{"id":"2303.12533","title":"Pixel-wise Agricultural Image Time Series Classification: Comparisons and a Deformable Prototype-based Approach","created":"2023-03-22","cited_by_count":8,"area":null},{"id":"2305.12011","title":"Boosting Crop Classification by Hierarchically Fusing Satellite, Rotational, and Contextual Data","created":"2023-05-19","cited_by_count":8,"area":null},{"id":"2201.08789","title":"AiTLAS: Artificial Intelligence Toolbox for Earth Observation","created":"2022-01-21","cited_by_count":7,"area":null},{"id":"2212.08208","title":"Location-aware Adaptive Normalization: A Deep Learning Approach For Wildfire Danger Forecasting","created":"2022-12-16","cited_by_count":7,"area":null},{"id":"2111.09902","title":"A transformer-based model for default prediction in mid-cap corporate markets","created":"2021-11-18","cited_by_count":6,"area":null},{"id":"2305.02086","title":"Revisiting the Encoding of Satellite Image Time Series","created":"2023-05-03","cited_by_count":6,"area":null},{"id":"2407.08448","title":"Paving the way toward foundation models for irregular and unaligned Satellite Image Time Series","created":"2024-07-11","cited_by_count":6,"area":null},{"id":"2502.15122","title":"MONSTER: Monash Scalable Time Series Evaluation Repository","created":"2025-02-21","cited_by_count":6,"area":null},{"id":"2204.11301","title":"Satellite Image Time Series Analysis for Big Earth Observation Data","created":"2022-04-24","cited_by_count":5,"area":null},{"id":"2401.07398","title":"Cross Domain Early Crop Mapping using CropSTGAN","created":"2024-01-15","cited_by_count":4,"area":null},{"id":"2409.09673","title":"SITSMamba for Crop Classification based on Satellite Image Time Series","created":"2024-09-15","cited_by_count":4,"area":"ssm"},{"id":"2502.17066","title":"DUNIA: Pixel-Sized Embeddings via Cross-Modal Alignment for Earth Observation Applications","created":"2025-02-24","cited_by_count":4,"area":null},{"id":"2205.07721","title":"Towards Space-to-Ground Data Availability for Agriculture Monitoring","created":"2022-05-16","cited_by_count":3,"area":null},{"id":"2212.13596","title":"Semi-supervised multiscale dual-encoding method for faulty traffic data detection","created":"2022-12-27","cited_by_count":3,"area":null},{"id":"2305.13472","title":"A comprehensive theoretical framework for the optimization of neural networks classification performance with respect to weighted metrics","created":"2023-05-22","cited_by_count":3,"area":null},{"id":"2408.08887","title":"Tree species classification at the pixel-level using deep learning and multispectral time series in an imbalanced context","created":"2024-08-05","cited_by_count":3,"area":null},{"id":"2608.09497","title":"SwissCrop25: A National Multi-Year Benchmark for Operational Crop Mapping","created":"2026-08-10","cited_by_count":3,"area":null},{"id":"2204.08461","title":"Investigating Temporal Convolutional Neural Networks for Satellite Image Time Series Classification: A survey","created":"2022-04-13","cited_by_count":2,"area":null},{"id":"2205.00701","title":"DeepGraviLens: a Multi-Modal Architecture for Classifying Gravitational Lensing Data","created":"2022-05-02","cited_by_count":2,"area":null},{"id":"2404.11114","title":"Reuse out-of-year data to enhance land cover mapping via feature disentanglement and contrastive learning","created":"2024-04-17","cited_by_count":2,"area":null},{"id":"2409.09432","title":"Detecting Looted Archaeological Sites from Satellite Image Time Series","created":"2024-09-14","cited_by_count":2,"area":null},{"id":"2505.18355","title":"X-MethaneWet: A Cross-scale Global Wetland Methane Emission Benchmark Dataset for Advancing Science Discovery with AI","created":"2025-05-23","cited_by_count":2,"area":null},{"id":"2510.19579","title":"Multi-modal Co-learning for Earth Observation: Enhancing single-modality models via modality collaboration","created":"2025-10-22","cited_by_count":2,"area":null},{"id":"2512.11524","title":"Super-Resolved Canopy Height Mapping from Sentinel-2 Time Series Using Airborne LiDAR HD Reference Data across Metropolitan France","created":"2025-12-12","cited_by_count":2,"area":null},{"id":"2103.10050","title":"Spatio-temporal Crop Classification On Volumetric Data","created":"2021-03-18","cited_by_count":1,"area":null},{"id":"2107.14235","title":"EEG multipurpose eye blink detector using convolutional neural network","created":"2021-07-29","cited_by_count":1,"area":null},{"id":"2301.01520","title":"Towards Explainable Land Cover Mapping: a Counterfactual-based Strategy","created":"2023-01-04","cited_by_count":1,"area":null},{"id":"2309.07992","title":"An Automated Machine Learning Approach for Detecting Anomalous Peak Patterns in Time Series Data from a Research Watershed in the Northeastern United States Critical Zone","created":"2023-09-14","cited_by_count":1,"area":null},{"id":"2403.16582","title":"In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing Data","created":"2024-03-25","cited_by_count":1,"area":null},{"id":"2406.16513","title":"Multi-Modal Vision Transformers for Crop Mapping from Satellite Image Time Series","created":"2024-06-24","cited_by_count":1,"area":null},{"id":"2508.11919","title":"TimeSenCLIP: A Time Series Vision-Language Model for Remote Sensing","created":"2025-08-16","cited_by_count":1,"area":"mllm"},{"id":"2508.18829","title":"Assessing the Effectiveness of Deep Embeddings for Tree Species Classification in the Dutch Forest Inventory","created":"2025-08-26","cited_by_count":1,"area":null},{"id":"2509.03497","title":"Invariant Features for Global Crop Type Classification","created":"2025-09-03","cited_by_count":1,"area":null},{"id":"2602.07579","title":"Enhancing Time Series Classification with Diversity-Driven Neural Network Ensembles","created":"2026-02-07","cited_by_count":1,"area":null},{"id":"2602.19608","title":"Satellite-Based Detection of Looted Archaeological Sites Using Machine Learning","created":"2026-02-23","cited_by_count":1,"area":null},{"id":"2102.07280","title":"3D Fully Convolutional Neural Networks with Intersection Over Union Loss for Crop Mapping from Multi-Temporal Satellite Images","created":"2021-02-15","cited_by_count":0,"area":null},{"id":"2103.09588","title":"An Efficient Method for the Classification of Croplands in Scarce-Label Regions","created":"2021-03-17","cited_by_count":0,"area":null},{"id":"2103.16836","title":"Channel-Based Attention for LCC Using Sentinel-2 Time Series","created":"2021-03-31","cited_by_count":0,"area":null},{"id":"2112.11367","title":"Deep Learning and Earth Observation to Support the Sustainable Development Goals","created":"2021-12-21","cited_by_count":0,"area":null},{"id":"2203.16149","title":"Tampered VAE for Improved Satellite Image Time Series Classification","created":"2022-03-30","cited_by_count":0,"area":null},{"id":"2209.02797","title":"Fusion of Satellite Images and Weather Data with Transformer Networks for Downy Mildew Disease Detection","created":"2022-09-06","cited_by_count":0,"area":null},{"id":"2310.17657","title":"Deep Learning Algorithm for Advanced Level-3 Inverse-Modeling of Silicon-Carbide Power MOSFET Devices","created":"2023-10-16","cited_by_count":0,"area":null},{"id":"2312.10068","title":"Artificial Neural Network for Estimation of Physical Parameters of Sea Water using LiDAR Waveforms","created":"2023-12-05","cited_by_count":0,"area":null},{"id":"2408.01607","title":"Deep Learning Meets OBIA: Tasks, Challenges, Strategies, and Perspectives","created":"2024-08-02","cited_by_count":0,"area":null},{"id":"2503.00358","title":"CRUPL: A Semi-Supervised Cyber Attack Detection with Consistency Regularization and Uncertainty-aware Pseudo-Labeling in Smart Grid","created":"2025-03-01","cited_by_count":0,"area":null},{"id":"2503.19719","title":"On What Depends the Robustness of Multi-source Models to Missing Data in Earth Observation?","created":"2025-03-25","cited_by_count":0,"area":null},{"id":"2505.16685","title":"On the use of Graphs for Satellite Image Time Series","created":"2025-05-22","cited_by_count":0,"area":null},{"id":"2508.02839","title":"Spatial-Temporal-Spectral Mamba with Sparse Deformable Token Sequence for Enhanced MODIS Time Series Classification","created":"2025-07-29","cited_by_count":0,"area":"ssm"},{"id":"2510.07008","title":"Bayesian Modelling of Multi-Year Crop Type Classification Using Deep Neural Networks and Hidden Markov Models","created":"2025-10-08","cited_by_count":0,"area":null},{"id":"2510.21813","title":"SITS-DECO: A Generative Decoder Is All You Need For Multitask Satellite Image Time Series Modelling","created":"2025-10-21","cited_by_count":0,"area":null},{"id":"2601.04956","title":"TEA: Temporal Adaptive Satellite Image Semantic Segmentation","created":"2026-01-08","cited_by_count":0,"area":null},{"id":"2601.06197","title":"AI Safeguards, Generative AI and the Pandora Box: AI Safety Measures to Protect Businesses and Personal Reputation","created":"2026-01-08","cited_by_count":0,"area":null},{"id":"2603.12073","title":"A Multi-Label Temporal Convolutional Framework for Transcription Factor Binding Characterization","created":"2026-03-12","cited_by_count":0,"area":null},{"id":"2604.07953","title":"Pruning Extensions and Efficiency Trade-Offs for Sustainable Time Series Classification","created":"2026-04-09","cited_by_count":0,"area":null},{"id":"2608.00870","title":"PhenoStitch: Training-Free Panoptic Crop Mapping from Satellite Image Time Series","created":"2026-08-01","cited_by_count":0,"area":null},{"id":"2608.05979","title":"Multi-Year Geospatial Reasoning using Interannually-Consistent Historical Predictions as a Free Input Modality","created":"2026-08-06","cited_by_count":0,"area":null},{"id":"2608.27175","title":"Temporal Sensitivity Analysis of Tessera Embeddings","created":"2026-08-27","cited_by_count":0,"area":null},{"id":"2609.13453","title":"A Machine Learning API for Earth Observation Data Cubes Based on openEO","created":"2026-09-11","cited_by_count":0,"area":null},{"id":"2609.16871","title":"SPEAR NeXT Causal Latent Forecasting Across Multiple Horizons for Spectral Temporal Earth Representation Learning","created":"2026-09-15","cited_by_count":0,"area":null},{"id":"2609.38165","title":"Cropland PAtteRNS: Parallel Dimensional Attention Networks and Attention to Dataset Disparity for Crop Segmentation in Satellite Imagery Time Series Data","created":"2026-09-29","cited_by_count":0,"area":null}],"next_cursor":null}