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

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

Buchholz, T-O, Krull, A, Shahidi, R, Pigino, G, Jékely, G & Jug, F 2019, 'Content-aware image restoration for electron microscopy', Methods in Cell Biology, vol. 152, pp. 277-289.

Cojoc, G, Florescu, A-M, Krull, A, Klemm, AH, Pavin, N, Jülicher, F & Tolić, IM 2016, 'Paired arrangement of kinetochores together with microtubule pivoting and dynamics drive kinetochore capture in meiosis I', Scientific Reports, vol. 6, no. 1, pp. 1-12.

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

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.

Krull, A, Buchholz, T-O & Jug, F 2019, Noise2void-learning denoising from single noisy images. in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 2129-2137. <https://openaccess.thecvf.com/content_CVPR_2019/papers/Krull_Noise2Void_-_Learning_Denoising_From_Single_Noisy_Images_CVPR_2019_paper.pdf>

Brachmann, E, Krull, A, Nowozin, S, Shotton, J, Michel, F, Gumhold, S & Rother, C 2017, Dsac-differentiable ransac for camera localization. in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 6684-6692.

Michel, F, Kirillov, A, Brachmann, E, Krull, A, Gumhold, S, Savchynskyy, B & Rother, C 2017, Global hypothesis generation for 6D object pose estimation. in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 462-471.

Krull, A, Brachmann, E, Nowozin, S, Michel, F, Shotton, J & Rother, C 2017, Poseagent: Budget-constrained 6d object pose estimation via reinforcement learning. in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 6702-6710.

Massiceti, D, Krull, A, Brachmann, E, Rother, C & Torr, PHS 2017, Random forests versus Neural Networks—What's best for camera localization? in 2017 IEEE International Conference on Robotics and Automation (ICRA). pp. 5118-5125.

Brachmann, E, Michel, F, Krull, A, Yang, MY & Gumhold, S 2016, Uncertainty-driven 6d pose estimation of objects and scenes from a single rgb image. in Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 3364-3372.

View all publications in research portal