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- W4287773684 abstract "A combinatory approach of two well-known fields: deep learning and semi supervised learning is presented, to tackle the land cover identification problem. The proposed methodology demonstrates the impact on the performance of deep learning models, when SSL approaches are used as performance functions during training. Obtained results, at pixel level segmentation tasks over orthoimages, suggest that SSL enhanced loss functions can be beneficial in models' performance." @default.
- W4287773684 created "2022-07-26" @default.
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- W4287773684 date "2020-05-30" @default.
- W4287773684 modified "2023-09-24" @default.
- W4287773684 title "Semi-Supervised Fine-Tuning for Deep Learning Models in Remote Sensing Applications" @default.
- W4287773684 doi "https://doi.org/10.48550/arxiv.2006.00345" @default.
- W4287773684 hasPublicationYear "2020" @default.
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