| Impact of adversarial examples on deep learning models for biomedical image segmentation U Ozbulak, A Van Messem, W De Neve Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 82 | 2019 |
| Pytorch cnn visualizations U Ozbulak GitHub repository, 2019 | 71 | 2019 |
| Know Your Self-supervised Learning: A Survey on Image-based Generative and Discriminative Training U Ozbulak, HJ Lee, B Boga, ET Anzaku, H Park, A Van Messem, ... Transactions on Machine Learning, 2023 | 35 | 2023 |
| Investigating the significance of adversarial attacks and their relation to interpretability for radar-based human activity recognition systems U Ozbulak, B Vandersmissen, A Jalalvand, I Couckuyt, A Van Messem, ... Computer Vision and Image Understanding 202, 103111, 2021 | 17 | 2021 |
| Perturbation analysis of gradient-based adversarial attacks U Ozbulak, M Gasparyan, W De Neve, A Van Messem Pattern Recognition Letters 135, 313-320, 2020 | 12 | 2020 |
| How the softmax output is misleading for evaluating the strength of adversarial examples U Ozbulak, W De Neve, A Van Messem 2018 Conference on Neural Information Processing Systems (NeurIPS) Workshop …, 2018 | 8 | 2018 |
| Evaluating Adversarial Attacks on ImageNet: A Reality Check on Misclassification Classes U Ozbulak, M Pintor, A Van Messem, W De Neve 2021 Conference on Neural Information Processing Systems (NeurIPS) Workshop …, 2021 | 7 | 2021 |
| Selection of Source Images Heavily Influences the Effectiveness of Adversarial Attacks U Ozbulak, ET Anzaku, W De Neve, A Van Messem 2021 British Machine Vision Conference (BMVC), 2021 | 5 | 2021 |
| Automatic detection of Trypanosomosis in thick blood smears using image pre-processing and deep learning T Jung, ET Anzaku, U Özbulak, S Magez, A Van Messem, W De Neve Intelligent Human Computer Interaction: 12th International Conference, IHCI …, 2021 | 5 | 2021 |
| Not all adversarial examples require a complex defense: Identifying over-optimized adversarial examples with IQR-based logit thresholding U Ozbulak, A Van Messem, W De Neve 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 4 | 2019 |
| Convolutional neural network visualizations U Ozbulak, A Stoken, H Wang, R Geirhos, P Jiang | 4 | 2019 |
| Assessing the reliability of point mutation as data augmentation for deep learning with genomic data H Lee, U Ozbulak, H Park, S Depuydt, W De Neve, J Vankerschaver BMC bioinformatics 25 (1), 170, 2024 | 3 | 2024 |
| Tryp: a dataset of microscopy images of unstained thick blood smears for trypanosome detection ET Anzaku, MA Mohammed, U Ozbulak, J Won, H Hong, ... Scientific Data 10 (1), 716, 2023 | 3 | 2023 |
| Exact Feature Collisions in Neural Networks U Ozbulak, M Gasparyan, S Rao, W De Neve, A Van Messem arXiv preprint arXiv:2205.15763, 2022 | 2 | 2022 |
| Regional Image Perturbation Reduces Lp Norms of Adversarial Examples While Maintaining Model-to-model Transferability U Ozbulak, J Peck, W De Neve, B Goossens, Y Saeys, A Van Messem 2020 International Conference on Machine Learning (ICML) Workshop on …, 2020 | 2 | 2020 |
| Mutate and observe: utilizing deep neural networks to investigate the impact of mutations on translation initiation U Ozbulak, HJ Lee, J Zuallaert, W De Neve, S Depuydt, J Vankerschaver Bioinformatics 39 (6), btad338, 2023 | 1 | 2023 |
| Color Flow Imaging Microscopy Improves Identification of Stress Sources of Protein Aggregates in Biopharmaceuticals M Cohrs, S Koak, Y Lee, YJ Sung, W De Neve, HL Svilenov, U Ozbulak International Workshop on Medical Optical Imaging and Virtual Microscopy …, 2024 | | 2024 |
| Evaluating Visual Explanations of Attention Maps for Transformer-Based Medical Imaging M Chung, JB Won, G Kim, Y Kim, U Ozbulak International Conference on Medical Image Computing and Computer-Assisted …, 2024 | | 2024 |
| Identifying Critical Tokens for Accurate Predictions in Transformer-Based Medical Imaging Models S Kang, J Vankerschaver, U Ozbulak International Workshop on Machine Learning in Medical Imaging, 169-179, 2024 | | 2024 |
| Self-supervised Benchmark Lottery on ImageNet: Do Marginal Improvements Translate to Improvements on Similar Datasets? U Ozbulak, ET Anzaku, S Kang, W De Neve, J Vankerschaver 2024 International Joint Conference on Neural Networks (IJCNN), 1-8, 2024 | | 2024 |
Wesley De NeveAssociate Professor at Ghent University (Belgium) & Ghent University Global Campus (Korea)Verified email at ugent.be