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Title: GitHub - ericyoc/dissertation_code_and_data: Hybrid Neural Network Defense Framework · GitHub

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Description: Hybrid Neural Network Defense Framework. Contribute to ericyoc/dissertation_code_and_data development by creating an account on GitHub.

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25 Commits	https://github.com/ericyoc/dissertation_code_and_data/commits/main/
	https://github.com/ericyoc/dissertation_code_and_data/commits/main/
EMNIST Adver Training Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/EMNIST%20Adver%20Training%20Defense
EMNIST Adver Training Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/EMNIST%20Adver%20Training%20Defense
EMNIST Input Trans Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/EMNIST%20Input%20Trans%20Defense
EMNIST Input Trans Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/EMNIST%20Input%20Trans%20Defense
EMNIST Random Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/EMNIST%20Random%20Defense
EMNIST Random Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/EMNIST%20Random%20Defense
MNIST Adver Training Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/MNIST%20Adver%20Training%20Defense
MNIST Adver Training Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/MNIST%20Adver%20Training%20Defense
MNIST Input Trans Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/MNIST%20Input%20Trans%20Defense
MNIST Input Trans Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/MNIST%20Input%20Trans%20Defense
MNIST Random Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/MNIST%20Random%20Defense
MNIST Random Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/MNIST%20Random%20Defense
TinyImageNet Adver Training Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/TinyImageNet%20Adver%20Training%20Defense
TinyImageNet Adver Training Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/TinyImageNet%20Adver%20Training%20Defense
TinyImageNet Input Trans Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/TinyImageNet%20Input%20Trans%20Defense
TinyImageNet Input Trans Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/TinyImageNet%20Input%20Trans%20Defense
TinyImageNet Random Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/TinyImageNet%20Random%20Defense
TinyImageNet Random Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/TinyImageNet%20Random%20Defense
TrafficSigns Adver Training Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/TrafficSigns%20Adver%20Training%20Defense
TrafficSigns Adver Training Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/TrafficSigns%20Adver%20Training%20Defense
TrafficSigns Input Trans Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/TrafficSigns%20Input%20Trans%20Defense
TrafficSigns Input Trans Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/TrafficSigns%20Input%20Trans%20Defense
TrafficSigns Random Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/TrafficSigns%20Random%20Defense
TrafficSigns Random Defense	https://github.com/ericyoc/dissertation_code_and_data/tree/main/TrafficSigns%20Random%20Defense
clean_models	https://github.com/ericyoc/dissertation_code_and_data/tree/main/clean_models
clean_models	https://github.com/ericyoc/dissertation_code_and_data/tree/main/clean_models
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dissertation_charts	https://github.com/ericyoc/dissertation_code_and_data/tree/main/dissertation_charts
Dissertation_Defense.pdf	https://github.com/ericyoc/dissertation_code_and_data/blob/main/Dissertation_Defense.pdf
Dissertation_Defense.pdf	https://github.com/ericyoc/dissertation_code_and_data/blob/main/Dissertation_Defense.pdf
README.md	https://github.com/ericyoc/dissertation_code_and_data/blob/main/README.md
README.md	https://github.com/ericyoc/dissertation_code_and_data/blob/main/README.md
dissertation_code_and_data_poc.ipynb	https://github.com/ericyoc/dissertation_code_and_data/blob/main/dissertation_code_and_data_poc.ipynb
dissertation_code_and_data_poc.ipynb	https://github.com/ericyoc/dissertation_code_and_data/blob/main/dissertation_code_and_data_poc.ipynb
visualizations_dissertation.ipynb	https://github.com/ericyoc/dissertation_code_and_data/blob/main/visualizations_dissertation.ipynb
visualizations_dissertation.ipynb	https://github.com/ericyoc/dissertation_code_and_data/blob/main/visualizations_dissertation.ipynb
README	https://github.com/ericyoc/dissertation_code_and_data
	https://github.com/ericyoc/dissertation_code_and_data#hybrid-neural-network-defense-framework
	https://www.python.org/downloads/
	https://pytorch.org/
	https://github.com/ericyoc/dissertation_code_and_data#motivateing-article
https://doi.org/10.1007/978-3-032-11153-1_4	https://doi.org/10.1007/978-3-032-11153-1_4
	https://github.com/ericyoc/dissertation_code_and_data#table-of-contents
Overview	https://github.com/ericyoc/dissertation_code_and_data#overview
Architecture	https://github.com/ericyoc/dissertation_code_and_data#architecture
Code Structure	https://github.com/ericyoc/dissertation_code_and_data#code-structure
Datasets	https://github.com/ericyoc/dissertation_code_and_data#datasets
Adversarial Attacks	https://github.com/ericyoc/dissertation_code_and_data#adversarial-attacks
Defense Mechanisms	https://github.com/ericyoc/dissertation_code_and_data#defense-mechanisms
Randomization Defense (4 Techniques)	https://github.com/ericyoc/dissertation_code_and_data#1-randomization-defense
Input Transformation Defense (5 Techniques)	https://github.com/ericyoc/dissertation_code_and_data#2-input-transformation-defense
Adversarial Training	https://github.com/ericyoc/dissertation_code_and_data#3-adversarial-training
Defense Comparison Matrix	https://github.com/ericyoc/dissertation_code_and_data#defense-comparison-matrix
Installation	https://github.com/ericyoc/dissertation_code_and_data#installation
Usage	https://github.com/ericyoc/dissertation_code_and_data#usage
Defense Configuration Examples	https://github.com/ericyoc/dissertation_code_and_data#defense-configuration-examples
Running Experiments	https://github.com/ericyoc/dissertation_code_and_data#running-experiments
Key Features	https://github.com/ericyoc/dissertation_code_and_data#key-features
Technical Details	https://github.com/ericyoc/dissertation_code_and_data#technical-details
Performance Characteristics	https://github.com/ericyoc/dissertation_code_and_data#performance-characteristics
Defense Implementation Details	https://github.com/ericyoc/dissertation_code_and_data#defense-implementation-details
Configuration	https://github.com/ericyoc/dissertation_code_and_data#configuration
Global Configuration Variables	https://github.com/ericyoc/dissertation_code_and_data#global-configuration-variables
Complete Configuration Reference	https://github.com/ericyoc/dissertation_code_and_data#complete-configuration-reference
Output	https://github.com/ericyoc/dissertation_code_and_data#output
	https://github.com/ericyoc/dissertation_code_and_data#overview
	https://github.com/ericyoc/dissertation_code_and_data#research-goals
	https://github.com/ericyoc/dissertation_code_and_data#defense-configuration-summary
	https://github.com/ericyoc/dissertation_code_and_data#architecture
	https://github.com/ericyoc/dissertation_code_and_data#hybrid-neural-network-hnn
	https://github.com/ericyoc/dissertation_code_and_data#classical-component-cnn
	https://github.com/ericyoc/dissertation_code_and_data#quantum-component
	https://github.com/ericyoc/dissertation_code_and_data#hybrid-combination
	https://github.com/ericyoc/dissertation_code_and_data#code-structure
	https://github.com/ericyoc/dissertation_code_and_data#critical-code-sections
	https://github.com/ericyoc/dissertation_code_and_data#1-trainval-class-synchronization-lines-1120-1145
	https://github.com/ericyoc/dissertation_code_and_data#2-label-map-synchronization-lines-1901-2885
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	https://github.com/ericyoc/dissertation_code_and_data#4-hybrid-forward-pass-lines-251-290
	https://github.com/ericyoc/dissertation_code_and_data#datasets
	https://github.com/ericyoc/dissertation_code_and_data#mnist
	https://github.com/ericyoc/dissertation_code_and_data#emnist-digits
	https://github.com/ericyoc/dissertation_code_and_data#trafficsigns
	https://github.com/ericyoc/dissertation_code_and_data#tinyimagenet
	https://github.com/ericyoc/dissertation_code_and_data#adversarial-attacks
	https://github.com/ericyoc/dissertation_code_and_data#implemented-attacks
	https://github.com/ericyoc/dissertation_code_and_data#1-fast-gradient-sign-method-fgsm
	https://github.com/ericyoc/dissertation_code_and_data#2-projected-gradient-descent-pgd
	https://github.com/ericyoc/dissertation_code_and_data#3-carlini-wagner-cw
	https://github.com/ericyoc/dissertation_code_and_data#compound-attacks
	https://github.com/ericyoc/dissertation_code_and_data#defense-mechanisms
	https://github.com/ericyoc/dissertation_code_and_data#1-randomization-defense
	https://github.com/ericyoc/dissertation_code_and_data#11-random-resizing-random_resizing
	https://github.com/ericyoc/dissertation_code_and_data#12-random-cropping-random_cropping
	https://github.com/ericyoc/dissertation_code_and_data#13-random-rotation-random_rotation
	https://github.com/ericyoc/dissertation_code_and_data#14-combined-randomization-combined_randomization
	https://github.com/ericyoc/dissertation_code_and_data#2-input-transformation-defense
	https://github.com/ericyoc/dissertation_code_and_data#21-image-quilting-image_quilting
	https://github.com/ericyoc/dissertation_code_and_data#22-jpeg-compression-jpeg_compression
	https://github.com/ericyoc/dissertation_code_and_data#23-bit-depth-reduction-bit_depth_reduction
	https://github.com/ericyoc/dissertation_code_and_data#24-gaussian-noise-defense-gaussian_noise_defense
	https://github.com/ericyoc/dissertation_code_and_data#25-combined-input-transformation-combined_input_transformation
	https://github.com/ericyoc/dissertation_code_and_data#3-adversarial-training
	https://github.com/ericyoc/dissertation_code_and_data#method
	https://github.com/ericyoc/dissertation_code_and_data#process
	https://github.com/ericyoc/dissertation_code_and_data#characteristics
	https://github.com/ericyoc/dissertation_code_and_data#defense-selection-strategy
	https://github.com/ericyoc/dissertation_code_and_data#defense-comparison-matrix
	https://github.com/ericyoc/dissertation_code_and_data#installation
	https://github.com/ericyoc/dissertation_code_and_data#requirements
	https://github.com/ericyoc/dissertation_code_and_data#setup
	https://github.com/ericyoc/dissertation_code_and_data#google-drive-structure-recommended
	https://github.com/ericyoc/dissertation_code_and_data#usage
	https://github.com/ericyoc/dissertation_code_and_data#basic-execution
	https://github.com/ericyoc/dissertation_code_and_data#defense-configuration-examples
	https://github.com/ericyoc/dissertation_code_and_data#example-1-randomization-with-random-resizing
	https://github.com/ericyoc/dissertation_code_and_data#example-2-randomization-with-combined-techniques
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	https://github.com/ericyoc/dissertation_code_and_data#configuration-parameters
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	https://github.com/ericyoc/dissertation_code_and_data#adversarial-attacks-1
	https://github.com/ericyoc/dissertation_code_and_data#defense-settings
	https://github.com/ericyoc/dissertation_code_and_data#complete-configuration-reference
	https://github.com/ericyoc/dissertation_code_and_data#all-valid-configurations
	https://github.com/ericyoc/dissertation_code_and_data#experiment-matrix
	https://github.com/ericyoc/dissertation_code_and_data#complete-experiment-space
	https://github.com/ericyoc/dissertation_code_and_data#running-experiments
	https://github.com/ericyoc/dissertation_code_and_data#single-configuration
	https://github.com/ericyoc/dissertation_code_and_data#testing-all-randomization-techniques
	https://github.com/ericyoc/dissertation_code_and_data#testing-all-input-transformation-techniques
	https://github.com/ericyoc/dissertation_code_and_data#complete-experiment-suite
	https://github.com/ericyoc/dissertation_code_and_data#key-features
	https://github.com/ericyoc/dissertation_code_and_data#1-automatic-model-management
	https://github.com/ericyoc/dissertation_code_and_data#2-gpu-acceleration
	https://github.com/ericyoc/dissertation_code_and_data#3-comprehensive-evaluation
	https://github.com/ericyoc/dissertation_code_and_data#4-flexible-architecture
	https://github.com/ericyoc/dissertation_code_and_data#5-reproducibility
	https://github.com/ericyoc/dissertation_code_and_data#technical-details
	https://github.com/ericyoc/dissertation_code_and_data#memory-management
	https://github.com/ericyoc/dissertation_code_and_data#tinyimagenet-optimizations
	https://github.com/ericyoc/dissertation_code_and_data#gpu-memory-usage-estimated
	https://github.com/ericyoc/dissertation_code_and_data#training-optimizations
	https://github.com/ericyoc/dissertation_code_and_data#learning-rate-scheduling
	https://github.com/ericyoc/dissertation_code_and_data#early-stopping
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LICENSE	https://github.com/ericyoc/dissertation_code_and_data/blob/main/LICENSE
	https://github.com/ericyoc/dissertation_code_and_data#acknowledgments
link.springer.com/chapter/10.1007/978-3-032-11153-1_4	https://link.springer.com/chapter/10.1007/978-3-032-11153-1_4
mnist	https://github.com/topics/mnist
convolutional-neural-networks	https://github.com/topics/convolutional-neural-networks
quantum-circuit	https://github.com/topics/quantum-circuit
emnist	https://github.com/topics/emnist
tinyimagenet	https://github.com/topics/tinyimagenet
hnn	https://github.com/topics/hnn
trafficsigns	https://github.com/topics/trafficsigns
compound-adversarial-attacks	https://github.com/topics/compound-adversarial-attacks
defenses-input-transformation	https://github.com/topics/defenses-input-transformation
defenses-randomization	https://github.com/topics/defenses-randomization
defenses-adversarial-training	https://github.com/topics/defenses-adversarial-training
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