Page 72 - AI for Good-Innovate for Impact

AI for Good-Innovate for Impact

[10]. Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous
Driving. Available online:https:// ui .adsabs .harvard .edu/ abs/ 2024arXiv240317301Z/ abstract

[11]. Adversarial Objectness Gradient Attacks in Real-time Object Detection Systems. Available
online: ieeexplore .ieee .org/ document/ 9325397

[12]. Defense Against Adversarial Attacks Using High-Level Representation Guided Denoiser.
Available online:ieeexplore .ieee .org/ document/ 8578289

[13]. Benchmarks: Semantic Segmentation Neural Network Verification and Objection Detection
Neural Network Verification in Perceptions Tasks of Autonomous Driving. Available online: link
.springer .com/ chapter/ 10 .1007/ 978 -3 -031 -46002 -9 _16

[14]. Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial
environment. Available online:doi .org/ 10 .1038/ s41467 -021 -21007 -8

[15]. FedCORE: Federated Learning for Cross-Organization Recommendation Ecosystem.
Available online:ieeexplore .ieee .org/ document/ 10443503

[16]. Hierarchical Trajectory Planning for Narrow-Space Automated Parking with Deep
Reinforcement Learning: A Federated Learning Scheme. Available online:mdpi .com/ 1424
-8220/ 23/ 8/ 4087

[17]. Adversarial Safety-Critical Scenario Generation using Naturalistic Human Driving Priors.
Available online:ieeexplore .ieee .org/ document/ 10328462

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