| Phocnet: A deep convolutional neural network for word spotting in handwritten documents S Sudholt, GA Fink 2016 15th International Conference on Frontiers in Handwriting Recognition …, 2016 | 320 | 2016 |
| Safety concerns and mitigation approaches regarding the use of deep learning in safety-critical perception tasks O Willers, S Sudholt, S Raafatnia, S Abrecht Computer Safety, Reliability, and Security. SAFECOMP 2020 Workshops: DECSoS …, 2020 | 101 | 2020 |
| Evaluating word string embeddings and loss functions for CNN-based word spotting S Sudholt, GA Fink 2017 14th iapr international conference on document analysis and recognition …, 2017 | 81 | 2017 |
| Attribute CNNs for word spotting in handwritten documents S Sudholt, GA Fink International journal on document analysis and recognition (ijdar) 21, 199-218, 2018 | 72 | 2018 |
| Learning deep representations for word spotting under weak supervision N Gurjar, S Sudholt, GA Fink 2018 13th IAPR international workshop on document analysis systems (DAS), 7-12, 2018 | 53* | 2018 |
| A modified isomap approach to manifold learning in word spotting S Sudholt, GA Fink German Conference on Pattern Recognition, 529-539, 2015 | 33 | 2015 |
| Word hypotheses for segmentation-free word spotting in historic document images L Rothacker, S Sudholt, E Rusakov, M Kasperidus, GA Fink 2017 14th IAPR International Conference on Document Analysis and Recognition …, 2017 | 25 | 2017 |
| Handwritten word image categorization with convolutional neural networks and spatial pyramid pooling JI Toledo, S Sudholt, A Fornés, J Cucurull, GA Fink, J Lladós Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2016 | 19 | 2016 |
| Learning local image descriptors for word spotting S Sudholt, L Rothacker, GA Fink 2015 13th International Conference on Document Analysis and Recognition …, 2015 | 12 | 2015 |
| Expolring architectures for cnn-based word spotting E Rusakov, S Sudholt, F Wolf, GA Fink arXiv preprint arXiv:1806.10866, 2018 | 11 | 2018 |
| Query-by-online word spotting revisited: Using cnns for cross-domain retrieval S Sudholt, L Rothacker, GA Fink 2017 14th IAPR International Conference on Document Analysis and Recognition …, 2017 | 4 | 2017 |
| Optimistic and pessimistic neural networks for scene and object recognition R Grzeszick, S Sudholt, GA Fink arXiv preprint arXiv:1609.07982, 2016 | 4 | 2016 |
| Learning attribute representations with deep convolutional neural networks for word spotting S Sudholt | 3 | 2018 |
| Weakly supervised object detection with pointwise mutual information R Grzeszick, S Sudholt, GA Fink arXiv preprint arXiv:1801.08747, 2018 | 2 | 2018 |
| Optimistic and pessimistic neural networks for object recognition R Grzeszick, S Sudholt, GA Fink 2017 IEEE International Conference on Image Processing (ICIP), 350-354, 2017 | 1 | 2017 |
| Method for training an artificial neural network, artificial neural network, use of an artificial neural network, and corresponding computer program, machine-readable memory … O Willers, S Sudholt US Patent 11,699,075, 2023 | | 2023 |
| Method for determining a confidence value of a detected object O Willers, S Sudholt, S Raafatnia, S Abrecht US Patent 11,586,855, 2023 | | 2023 |
| Method and device for evaluating an image classifier C Heinzemann, C Gladisch, J Oehlerking, K Groh, M Woehrle, M Rittel, ... US Patent App. 17/790,578, 2023 | | 2023 |
| Method for estimating a global uncertainty of a neural network O Willers, S Sudholt, S Raafatnia, S Abrecht US Patent 11,531,899, 2022 | | 2022 |
| Method for calculating a quality measure for assessing an object detection algorithm O Willers, S Sudholt US Patent App. 17/777,222, 2022 | | 2022 |
