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  • Current trends in deep learning for Earth observation [Elektronski vir] : an open-source benchmark arena for image classification
    Dimitrovski, Ivica ...
    We present AiTLAS: Benchmark Arena – an open-source benchmark suite for evaluating state-of-the-art deep learning approaches for image classification in Earth Observation (EO). To this end, we ... present a comprehensive comparative analysis of more than 500 models derived from ten different state-of-the-art architectures and compare them to a variety of multi-class and multi-label classification tasks from 22 datasets with different sizes and properties. In addition to models trained entirely on these datasets, we benchmark models trained in the context of transfer learning, leveraging pre-trained model variants, as it is typically performed in practice. All presented approaches are general and can be easily extended to many other remote sensing image classification tasks not considered in this study. To ensure reproducibility and facilitate better usability and further developments, all of the experimental resources including the trained models, model configurations, and processing details of the datasets (with their corresponding splits used for training and evaluating the models) are publicly available on the repository: https://github.com/biasvariancelabs/aitlas-arena.
    Source: ISPRS Journal of Photogrammetry and Remote Sensing [Elektronski vir]. - ISSN 1872-8235 (Vol. 197, Mar. 2023, str. 18-35)
    Type of material - e-article ; adult, serious
    Publish date - 2023
    Language - english
    COBISS.SI-ID - 140788995
    DOI

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