CNN-based passive traffic analysis fails to deanonymize I2P services in both lab and real-world tests.
Conceptual Understanding of Convolutional Neural Network – A Deep Learning Approach
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IA-QCNN applies quantum principles via ring-topology convolution and importance weighting to achieve claimed high-accuracy MGMT methylation prediction from MRI with fewer parameters and noise robustness than classical models.
citing papers explorer
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Convolutional-Neural-Networks for Deanonymisation of I2P Traffic
CNN-based passive traffic analysis fails to deanonymize I2P services in both lab and real-world tests.
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A Specialized Importance-Aware Quantum Convolutional Neural Network with Ring-Topology (IA-QCNN) for MGMT Promoter Methylation Prediction in Glioblastoma
IA-QCNN applies quantum principles via ring-topology convolution and importance weighting to achieve claimed high-accuracy MGMT methylation prediction from MRI with fewer parameters and noise robustness than classical models.