BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

303 related articles for article (PubMed ID: 34748482)

  • 21. Uni-image: Universal image construction for robust neural model.
    Ho J; Lee BG; Kang DK
    Neural Netw; 2020 Aug; 128():279-287. PubMed ID: 32454372
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Adv-BDPM: Adversarial attack based on Boundary Diffusion Probability Model.
    Zhang D; Dong Y
    Neural Netw; 2023 Oct; 167():730-740. PubMed ID: 37729788
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Enhancing adversarial defense for medical image analysis systems with pruning and attention mechanism.
    Chen L; Zhao L; Chen CY
    Med Phys; 2021 Oct; 48(10):6198-6212. PubMed ID: 34487364
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Natural Images Allow Universal Adversarial Attacks on Medical Image Classification Using Deep Neural Networks with Transfer Learning.
    Minagi A; Hirano H; Takemoto K
    J Imaging; 2022 Feb; 8(2):. PubMed ID: 35200740
    [TBL] [Abstract][Full Text] [Related]  

  • 25. SMGEA: A New Ensemble Adversarial Attack Powered by Long-Term Gradient Memories.
    Che Z; Borji A; Zhai G; Ling S; Li J; Min X; Guo G; Le Callet P
    IEEE Trans Neural Netw Learn Syst; 2022 Mar; 33(3):1051-1065. PubMed ID: 33296311
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Adversarial Patch Attacks on Deep-Learning-Based Face Recognition Systems Using Generative Adversarial Networks.
    Hwang RH; Lin JY; Hsieh SY; Lin HY; Lin CL
    Sensors (Basel); 2023 Jan; 23(2):. PubMed ID: 36679651
    [TBL] [Abstract][Full Text] [Related]  

  • 27. An Optimized Black-Box Adversarial Simulator Attack Based on Meta-Learning.
    Chen Z; Ding J; Wu F; Zhang C; Sun Y; Sun J; Liu S; Ji Y
    Entropy (Basel); 2022 Sep; 24(10):. PubMed ID: 37420397
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Robustifying Deep Networks for Medical Image Segmentation.
    Liu Z; Zhang J; Jog V; Loh PL; McMillan AB
    J Digit Imaging; 2021 Oct; 34(5):1279-1293. PubMed ID: 34545476
    [TBL] [Abstract][Full Text] [Related]  

  • 29. A Dual Robust Graph Neural Network Against Graph Adversarial Attacks.
    Tao Q; Liao J; Zhang E; Li L
    Neural Netw; 2024 Jul; 175():106276. PubMed ID: 38599138
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Adversarial attack vulnerability of medical image analysis systems: Unexplored factors.
    Bortsova G; González-Gonzalo C; Wetstein SC; Dubost F; Katramados I; Hogeweg L; Liefers B; van Ginneken B; Pluim JPW; Veta M; Sánchez CI; de Bruijne M
    Med Image Anal; 2021 Oct; 73():102141. PubMed ID: 34246850
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Learning defense transformations for counterattacking adversarial examples.
    Li J; Zhang S; Cao J; Tan M
    Neural Netw; 2023 Jul; 164():177-185. PubMed ID: 37149918
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Towards Robustifying Image Classifiers against the Perils of Adversarial Attacks on Artificial Intelligence Systems.
    Anastasiou T; Karagiorgou S; Petrou P; Papamartzivanos D; Giannetsos T; Tsirigotaki G; Keizer J
    Sensors (Basel); 2022 Sep; 22(18):. PubMed ID: 36146258
    [TBL] [Abstract][Full Text] [Related]  

  • 33. ApaNet: adversarial perturbations alleviation network for face verification.
    Sun G; Hu H; Su Y; Liu Q; Lu X
    Multimed Tools Appl; 2023; 82(5):7443-7461. PubMed ID: 36035322
    [TBL] [Abstract][Full Text] [Related]  

  • 34. A Distributed Black-Box Adversarial Attack Based on Multi-Group Particle Swarm Optimization.
    Suryanto N; Kang H; Kim Y; Yun Y; Larasati HT; Kim H
    Sensors (Basel); 2020 Dec; 20(24):. PubMed ID: 33327453
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Crafting Adversarial Perturbations via Transformed Image Component Swapping.
    Agarwal A; Ratha N; Vatsa M; Singh R
    IEEE Trans Image Process; 2022; 31():7338-7349. PubMed ID: 36094979
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Machine learning through cryptographic glasses: combating adversarial attacks by key-based diversified aggregation.
    Taran O; Rezaeifar S; Holotyak T; Voloshynovskiy S
    EURASIP J Inf Secur; 2020; 2020(1):10. PubMed ID: 32685910
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Remix: Towards the transferability of adversarial examples.
    Zhao H; Hao L; Hao K; Wei B; Cai X
    Neural Netw; 2023 Jun; 163():367-378. PubMed ID: 37119676
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Adversarial attack on deep learning-based dermatoscopic image recognition systems: Risk of misdiagnosis due to undetectable image perturbations.
    Allyn J; Allou N; Vidal C; Renou A; Ferdynus C
    Medicine (Baltimore); 2020 Dec; 99(50):e23568. PubMed ID: 33327315
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Detecting the universal adversarial perturbations on high-density sEMG signals.
    Xue B; Wu L; Liu A; Zhang X; Chen X; Chen X
    Comput Biol Med; 2022 Oct; 149():105978. PubMed ID: 36037630
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Removing Adversarial Noise via Low-Rank Completion of High-Sensitivity Points.
    Zhao Z; Wang H; Sun H; Yuan J; Huang Z; He Z
    IEEE Trans Image Process; 2021; 30():6485-6497. PubMed ID: 34110994
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 16.