Dr Alexander Krull

Dr Alexander Krull

School of Computer Science
Lecturer in Data Science and AI

Contact details

Address
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Publications

Recent publications

Article

von Chamier, L, Laine, RF, Jukkala, J, Spahn, C, Krentzel, D, Nehme, E, Lerche, M, Hernández-Pérez, S, Mattila, PK, Karinou, E, Holden, S, Solak, AC, Krull, A, Buchholz, T-O, Jones, ML, Royer, LA, Leterrier, C, Shechtman, Y, Jug, F, Heilemann, M, Jacquemet, G & Henriques, R 2021, 'Democratising deep learning for microscopy with ZeroCostDL4Mic', Nature Communications, vol. 12, no. 1, 2276. https://doi.org/10.1038/s41467-021-22518-0

Laine, RF, Jacquemet, G & Krull, A 2021, 'Imaging in focus: an introduction to denoising bioimages in the era of deep learning', The International Journal of Biochemistry & Cell Biology, vol. 140, 106077. https://doi.org/10.1016/j.biocel.2021.106077

Krull, A, Hirsch, P, Rother, C, Schiffrin, A & Krull, C 2020, 'Artificial-intelligence-driven scanning probe microscopy', Communications Physics, vol. 3, no. 1, pp. 1-8.

Krull, A, Vičar, T, Prakash, M, Lalit, M & Jug, F 2020, 'Probabilistic noise2void: Unsupervised content-aware denoising', Frontiers in Computer Science, vol. 2, pp. 5. https://doi.org/10.3389/fcomp.2020.00005

Chapter

Buchholz, T-O, Prakash, M, Schmidt, D, Krull, A & Jug, F 2020, DenoiSeg: Joint Denoising and Segmentation. in DenoiSeg: Joint Denoising and Segmentation. https://doi.org/10.1007/978-3-030-66415-2_21

Goncharova, AS, Honigmann, A, Jug, F & Krull, A 2020, Improving Blind Spot Denoising for Microscopy. in Improving Blind Spot Denoising for Microscopy. https://doi.org/10.1007/978-3-030-66415-2_25

Conference contribution

Krull, A, Basevi, H, Salmon, B, Zeug, A, Müller, F, Tonks, S, Muppala, L & Leonardis, A 2024, Image Denoising and the Generative Accumulation of Photons. in 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE Workshop on Applications of Computer Vision (WACV), IEEE, pp. 1528-1537, 2024 IEEE/CVF Winter Conference on Applications of Computer Vision, Waikoloa, Hawaii, United States, 4/01/24. https://doi.org/10.1109/WACV57701.2024.00155

Cheng, X, Jia, X, Lu, W, Li, Q, Shen, L, Krull, A & Duan, J 2024, WiNet: Wavelet-Based Incremental Learning for Efficient Medical Image Registration. in Medical Image Computing and Computer Assisted Intervention – MICCAI 2024: 27th International Conference, Marrakesh, Morocco, October 6–10, 2024. Lecture Notes in Computer Science, vol. 15002, Springer, 27th International Conference on Medical Image Computing and Computer Assisted Intervention, Marrakesh, Morocco, 6/10/24. https://doi.org/10.1007/978-3-031-72069-7_71

Salmon, B & Krull, A 2023, Direct Unsupervised Denoising. in 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, IEEE, pp. 3840-3847, 2023 IEEE/CVF International Conference on Computer Vision (ICCV), Paris, France, 1/10/23. https://doi.org/10.1109/ICCVW60793.2023.00415

Tonks, S, Hsu, C, Hood, S, Musso, R, Hopely, C, Doan, M, Edwards, E, Krull, A & Styles, I 2023, Evaluating virtual staining for high-throughput screening. in 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)., 10230501, ISBI, IEEE, 20th IEEE International Symposium on Biomedical Imaging, Cartagena , Colombia, 18/04/23. https://doi.org/10.1109/ISBI53787.2023.10230501

Salmon, B & Krull, A 2023, Towards structured noise models for unsupervised denoising. in L Karlinsky, T Michaeli & K Nishino (eds), Computer Vision – ECCV 2022 Workshops: Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part IV. 1 edn, Lecture Notes in Computer Science, vol. 13804, Springer, Cham, pp. 379–394. https://doi.org/10.1007/978-3-031-25069-9_25

Prakash, M, Lalit, M, Tomancak, P, Krull, A & Jug, F 2020, Fully unsupervised probabilistic noise2void. in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). pp. 154-158.

Prakash, M, Buchholz, T-O, Lalit, M, Tomancak, P, Jug, F & Krull, A 2020, Leveraging self-supervised denoising for image segmentation. in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). pp. 428-432.

Broaddus, C, Krull, A, Weigert, M, Schmidt, U & Myers, G 2020, Removing structured noise with self-supervised blind-spot networks. in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). pp. 159-163.

Preprint

Salmon, B & Krull, A 2023 'Unsupervised Denoising for Signal-Dependent and Row-Correlated Imaging Noise' arXiv, pp. 1-32. https://doi.org/10.48550/arXiv.2310.07887

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