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Remote Sensing Target Fine-grained Classification (TFGC) is of great significance in both military and civilian fields.
Differential privacy
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Fedbe: Making bayesian model ensemble applicable to federated learning, 2021
Hong-You Chen and Wei-Lun Chao · 2021
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A public dataset for fine-grained ship classification in optical remote sensing images
Yanghua Di, Zhiguo Jiang, and Haopeng Zhang · 2021
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Ultralightweight spatial–spectral feature cooperation network for change detection in remote sensing images
Tao Lei, Xinzhe Geng, Hailong Ning, Zhiyong Lv, Maoguo Gong, Yaochu Jin, and Asoke K Nandi · 2023
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Review on security of federated learning and its application in healthcare
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A privacy preserving system for movie recommendations using federated learning
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Fine-grained object recognition using a combination model of navigator–teacher–scrutinizer and spinal networks
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Adap-emd: Adaptive emd for aircraft fine-grained classification in remote sensing
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Communication-efficient federated learning via knowledge distillation
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An explainable attention network for fine-grained ship classification using remote-sensing images
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Transformer and cnn hybrid deep neural network for semantic segmentation of very-high-resolution remote sensing imagery
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Learning across decentralized multi-modal remote sensing archives with federated learning
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Efm-net: An essential feature mining network for target fine-grained classification in optical remote sensing images
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Classification matters more: Global instance contrast for fine-grained sar aircraft detection
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Privacy-preserving federated learning of remote sensing image classification with dishonest-majority
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