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Adversarial machine learning

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Adversarial machine learning

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Automation of the diagnosis process in the railway system : Detection of defects in concrete sleepers using vision-based machine learning models

On the benefits of robust models in modulation recognition

The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing

Predictably Unequal? The Effects of Machine Learning on Credit Markets

POSEIDON: Privacy-Preserving Federated Neural Network Learning

Counting using deep learning regression gives value to ecological surveys

Generating Smooth Pose Sequences for Diverse Human Motion Prediction

Omnidata: A Scalable Pipeline for Making Multi-Task Mid-Level Vision Datasets from 3D Scans

CryoGAN: A New Reconstruction Paradigm for Single-Particle Cryo-EM Via Deep Adversarial Learning

Advances and Open Problems in Federated Learning