Evaluating the robustness of semantic segmentation for autonomous driving against real-world adversarial patch attacks
Deep learning and convolutional neural networks allow achieving impressive performance
in computer vision tasks, such as object detection and semantic segmentation (SS) …
in computer vision tasks, such as object detection and semantic segmentation (SS) …
Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World Adversarial Patch Attacks
F Nesti, G Rossolini, S Nair, A Biondi… - arXiv e …, 2021 - ui.adsabs.harvard.edu
Deep learning and convolutional neural networks allow achieving impressive performance
in computer vision tasks, such as object detection and semantic segmentation (SS) …
in computer vision tasks, such as object detection and semantic segmentation (SS) …
[引用][C] Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World Adversarial Patch Attacks
F Nesti, G Rossolini, S Nair, A Biondi… - 2022 IEEE/CVF Winter …, 2022 - iris.sssup.it
Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World
Adversarial Patch Attacks IRIS IRIS Home Sfoglia Macrotipologie & tipologie Autore Titolo …
Adversarial Patch Attacks IRIS IRIS Home Sfoglia Macrotipologie & tipologie Autore Titolo …
Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World Adversarial Patch Attacks
F Nesti, G Rossolini, S Nair, A Biondi… - 2022 IEEE/CVF Winter …, 2022 - computer.org
Deep learning and convolutional neural networks allow achieving impressive performance
in computer vision tasks, such as object detection and semantic segmentation (SS) …
in computer vision tasks, such as object detection and semantic segmentation (SS) …
[PDF][PDF] Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World Adversarial Patch Attacks
F Nesti, G Rossolini, S Nair, A Biondi, G Buttazzo - academia.edu
Deep learning and convolutional neural networks allow achieving impressive performance
in computer vision tasks, such as object detection and semantic segmentation (SS) …
in computer vision tasks, such as object detection and semantic segmentation (SS) …
Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World Adversarial Patch Attacks
F Nesti, G Rossolini, S Nair, A Biondi… - arXiv preprint arXiv …, 2021 - arxiv.org
Deep learning and convolutional neural networks allow achieving impressive performance
in computer vision tasks, such as object detection and semantic segmentation (SS) …
in computer vision tasks, such as object detection and semantic segmentation (SS) …
Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World Adversarial Patch Attacks
F Nesti, G Rossolini, S Nair, A Biondi… - 2022 IEEE/CVF Winter …, 2022 - ieeexplore.ieee.org
Deep learning and convolutional neural networks allow achieving impressive performance
in computer vision tasks, such as object detection and semantic segmentation (SS) …
in computer vision tasks, such as object detection and semantic segmentation (SS) …
[PDF][PDF] Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World Adversarial Patch Attacks
F Nesti, G Rossolini, S Nair, A Biondi, G Buttazzo - academia.edu
Deep learning and convolutional neural networks allow achieving impressive performance
in computer vision tasks, such as object detection and semantic segmentation (SS) …
in computer vision tasks, such as object detection and semantic segmentation (SS) …