| Transforming sensor data to the image domain for deep learning—An application to footstep detection MS Singh, V Pondenkandath, B Zhou, P Lukowicz, M Liwickit 2017 International Joint Conference on Neural Networks (IJCNN), 2665-2672, 2017 | 103 | 2017 |
| A comprehensive study of imagenet pre-training for historical document image analysis L Studer, M Alberti, V Pondenkandath, P Goktepe, T Kolonko, A Fischer, ... 2019 International Conference on Document Analysis and Recognition (ICDAR …, 2019 | 87 | 2019 |
| Combining graph edit distance and triplet networks for offline signature verification P Maergner, V Pondenkandath, M Alberti, M Liwicki, K Riesen, R Ingold, ... Pattern Recognition Letters 125, 527-533, 2019 | 65 | 2019 |
| Labeling, cutting, grouping: an efficient text line segmentation method for medieval manuscripts M Alberti, L Vögtlin, V Pondenkandath, M Seuret, R Ingold, M Liwicki 2019 International Conference on Document Analysis and Recognition (ICDAR …, 2019 | 45 | 2019 |
| Deepdiva: a highly-functional python framework for reproducible experiments M Alberti, V Pondenkandath, M Würsch, R Ingold, M Liwicki 2018 16th International Conference on Frontiers in Handwriting Recognition …, 2018 | 40 | 2018 |
| Subword semantic hashing for intent classification on small datasets K Shridhar, A Dash, A Sahu, GG Pihlgren, P Alonso, V Pondenkandath, ... 2019 International Joint Conference on Neural Networks (IJCNN), 1-6, 2019 | 39 | 2019 |
| Offline signature verification by combining graph edit distance and triplet networks P Maergner, V Pondenkandath, M Alberti, M Liwicki, K Riesen, R Ingold, ... Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2018 | 29 | 2018 |
| Historical document image segmentation with LDA-initialized deep neural networks M Alberti, M Seuret, V Pondenkandath, R Ingold, M Liwicki Proceedings of the 4th international workshop on historical document imaging …, 2017 | 26 | 2017 |
| Are you tampering with my data? M Alberti, V Pondenkandath, M Wursch, M Bouillon, M Seuret, R Ingold, ... Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018 | 23 | 2018 |
| Historical document synthesis with generative adversarial networks V Pondenkandath, M Alberti, M Diatta, R Ingold, M Liwicki 2019 International Conference on Document Analysis and Recognition Workshops …, 2019 | 21 | 2019 |
| Survey of artificial intelligence for card games and its application to the Swiss game Jass J Niklaus, M Alberti, V Pondenkandath, R Ingold, M Liwicki 2019 6th Swiss Conference on Data Science (SDS), 25-30, 2019 | 21 | 2019 |
| Generating synthetic handwritten historical documents with OCR constrained GANs L Vögtlin, M Drazyk, V Pondenkandath, M Alberti, R Ingold Document Analysis and Recognition–ICDAR 2021: 16th International Conference …, 2021 | 19 | 2021 |
| Identifying cross-depicted historical motifs V Pondenkandath, M Alberti, N Eichenberger, R Ingold, M Liwicki 2018 16th International Conference on Frontiers in Handwriting Recognition …, 2018 | 15 | 2018 |
| Exploiting state-of-the-art deep learning methods for document image analysis V Pondenkandath, M Seuret, R Ingold, MZ Afzal, M Liwicki 2017 14th IAPR International Conference on Document Analysis and Recognition …, 2017 | 14 | 2017 |
| Leveraging random label memorization for unsupervised pre-training V Pondenkandath, M Alberti, S Puran, R Ingold, M Liwicki arXiv preprint arXiv:1811.01640, 2018 | 12 | 2018 |
| Improving reproducible deep learning workflows with deepdiva M Alberti, V Pondenkandath, L Vögtlin, M Würsch, R Ingold, M Liwicki 2019 6th Swiss Conference on Data Science (SDS), 13-18, 2019 | 11 | 2019 |
| Cross-Depicted Historical Motif Categorization and Retrieval with Deep Learning V Pondenkandath, M Alberti, N Eichenberger, R Ingold, M Liwicki Journal of Imaging 6 (7), 71, 2020 | 7 | 2020 |
| Cobra: A cli tool to create and share reproducible projects L Vögtlin, V Pondenkandath, R Ingold 2020 7th Swiss Conference on Data Science (SDS), 47-48, 2020 | 4 | 2020 |
| Dnnviz: Training evolution visualization for deep neural network G Clavien, M Alberti, V Pondenkandath, R Ingold, M Liwicki 2019 6th Swiss Conference on Data Science (SDS), 19-24, 2019 | 4 | 2019 |
Marcus LiwickiLuleå University of Technology, EISLAB, Machine Learning, SwedenVerified email at ltu.se
