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DENETHOR: The DynamicEarthNET dataset for Harmonized, inter-Operable, analysis-Ready, daily crop monitoring from space.

, , , , , , , , , , , and . NeurIPS Datasets and Benchmarks, (2021)

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Reliable and Fast Recurrent Neural Network Architecture Optimization., , and . CoRR, (2021)Random error sampling-based recurrent neural network architecture optimization., , and . Eng. Appl. Artif. Intell., (2020)We Won't Get Fooled Again: When Performance Metric Malfunction Affects the Landscape of Hyperparameter Optimization Problems., , and . OLA, volume 1824 of Communications in Computer and Information Science, page 148-160. Springer, (2023)Comparing Deep Recurrent Networks Based on the MAE Random Sampling, a First Approach., , and . CAEPIA, volume 11160 of Lecture Notes in Computer Science, page 24-33. Springer, (2018)DC4Flood: A Deep Clustering Framework for Rapid Flood Detection Using Sentinel-1 SAR Imagery., , , and . IEEE Geosci. Remote. Sens. Lett., (2024)Tile map size optimization for real world routing by using differential evolution., , , and . CEC, page 1482-1488. IEEE, (2017)DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation., , , , , , , , , and 3 other author(s). CVPR, page 21126-21135. IEEE, (2022)JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network Training., , and . IEEE Access, (2019)HPO: We won't get fooled again., , and . CoRR, (2022)Road map partitioning for routing by using a micro steady state evolutionary algorithm., , and . Eng. Appl. Artif. Intell., (2018)