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Norm Equality in Deep Neural Networks",
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@article{bb142564,
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        TITLE = "Horizontal Flows and Manifold Stochastics in Geometric Deep Learning",
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@article{bb142565,
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@article{bb142566,
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        TITLE = "Manifold-Based Multi-Deep Belief Network for Feature Extraction of
Hyperspectral Image",
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        BIBSOURCE = "http://www.visionbib.com/bibliography/pattern652dee2.html#TT138559"}

@article{bb142567,
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        AUTHOR = "Pai, G. and Talmon, R. and Bronstein, A.M. and Kimmel, R.",
        TITLE = "DIMAL: Deep Isometric Manifold Learning Using Sparse Geodesic
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@article{bb142571,
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        TITLE = "Deep Declarative Networks",
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@article{bb142572,
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@article{bb142573,
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        TITLE = "Model-Centric Data Manifold: The Data Through the Eyes of the Model",
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        BIBSOURCE = "http://www.visionbib.com/bibliography/pattern652dee2.html#TT138566"}

@article{bb142574,
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        TITLE = "Deep Learning Classification by ResNet-18 Based on the Real Spectral
Dataset from Multispectral Remote Sensing Images",
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        BIBSOURCE = "http://www.visionbib.com/bibliography/pattern652dee2.html#TT138567"}

@article{bb142575,
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@article{bb142576,
        AUTHOR = "Ning, X. and Tian, W.J. and He, F. and Bai, X. and Sun, L. and Li, W.J.",
        TITLE = "Hyper-sausage coverage function neuron model and learning algorithm
for image classification",
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@article{bb142577,
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        TITLE = "Random image frequency aggregation dropout in image classification
for deep convolutional neural networks",
        JOURNAL = CVIU,
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@article{bb142578,
        AUTHOR = "Nam, J.H. and Lee, S.C.",
        TITLE = "FSDA: Frequency re-scaling in data augmentation for corruption-robust
image classification",
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@article{bb142579,
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@article{bb142581,
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        TITLE = "Hierarchical Optimization-Derived Learning",
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@article{bb142582,
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@inproceedings{bb142584,
        AUTHOR = "Xu, K.J. and Chen, J.L. and Ning, Y. and Tang, W.",
        TITLE = "Deep Learning in Image Classification: An Overview",
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@inproceedings{bb142585,
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@inproceedings{bb142586,
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@inproceedings{bb142587,
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@inproceedings{bb142588,
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@inproceedings{bb142589,
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@inproceedings{bb142590,
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@inproceedings{bb142591,
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@inproceedings{bb142592,
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@inproceedings{bb142593,
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@inproceedings{bb142594,
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@inproceedings{bb142595,
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@inproceedings{bb142596,
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@inproceedings{bb142597,
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@inproceedings{bb142598,
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@inproceedings{bb142599,
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