Experimental assessment of аdversarial attacks to the deep neural networks in medical image recognition
This paper addresses the problem of dependence of the success rate of adversarial attacks to the deep neural networks on the biomedical image type and control parameters of generation of adversarial examples. With this work we are going to contribute towards accumulation of experimental results on a...
Saved in:
Main Authors: | D. M. Voynov, V. A. Kovalev |
---|---|
Format: | Article |
Language: | Russian |
Published: |
National Academy of Sciences of Belarus, the United Institute of Informatics Problems
2019-09-01
|
Series: | Informatika |
Subjects: | |
Online Access: | https://inf.grid.by/jour/article/view/876 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Visibility Enhancement of Lesion Regions in Chest X-Ray Images With Image Fidelity Preservation
by: Ryoichi Ishikawa, et al.
Published: (2025-01-01) -
APDL: an adaptive step size method for white-box adversarial attacks
by: Jiale Hu, et al.
Published: (2025-01-01) -
Modified AlexNet Convolution Neural Network For Covid-19 Detection Using Chest X-ray Images
by: Shadman Q. Salih, et al.
Published: (2020-06-01) -
Learning deep forest for face anti-spoofing: An alternative to the neural network against adversarial attacks
by: Rizhao Cai, et al.
Published: (2024-10-01) -
Three-dimensional structure of entire hydrated murine hearts at histological resolution
by: Jasper Frohn, et al.
Published: (2025-01-01)