| Survey and performance analysis of deep learning based object detection in challenging environments M Ahmed, KA Hashmi, A Pagani, M Liwicki, D Stricker, MZ Afzal Sensors 21 (15), 5116, 2021 | 88 | 2021 |
| Current status and performance analysis of table recognition in document images with deep neural networks KA Hashmi, M Liwicki, D Stricker, MA Afzal, MA Afzal, MZ Afzal IEEE Access 9, 87663-87685, 2021 | 72 | 2021 |
| Guided table structure recognition through anchor optimization KA Hashmi, D Stricker, M Liwicki, MN Afzal, MZ Afzal IEEE Access 9, 113521-113534, 2021 | 43 | 2021 |
| A survey of graphical page object detection with deep neural networks J Bhatt, KA Hashmi, MZ Afzal, D Stricker Applied Sciences 11 (12), 5344, 2021 | 40 | 2021 |
| HybridTabNet: Towards better table detection in scanned document images D Nazir, KA Hashmi, A Pagani, M Liwicki, D Stricker, MZ Afzal Applied Sciences 11 (18), 8396, 2021 | 36 | 2021 |
| Object detection with transformers: A review T Shehzadi, KA Hashmi, D Stricker, MZ Afzal arXiv preprint arXiv:2306.04670, 2023 | 33 | 2023 |
| Castabdetectors: Cascade network for table detection in document images with recursive feature pyramid and switchable atrous convolution KA Hashmi, A Pagani, M Liwicki, D Stricker, MZ Afzal Journal of Imaging 7 (10), 214, 2021 | 30 | 2021 |
| Featenhancer: Enhancing hierarchical features for object detection and beyond under low-light vision KA Hashmi, G Kallempudi, D Stricker, MZ Afzal Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 27 | 2023 |
| Cascade network with deformable composite backbone for formula detection in scanned document images KA Hashmi, A Pagani, M Liwicki, D Stricker, MZ Afzal Applied Sciences 11 (16), 7610, 2021 | 26 | 2021 |
| Towards robust object detection in floor plan images: A data augmentation approach S Mishra, KA Hashmi, A Pagani, M Liwicki, D Stricker, MZ Afzal Applied Sciences 11 (23), 11174, 2021 | 23 | 2021 |
| Sparse semi-DETR: sparse learnable queries for semi-supervised object detection T Shehzadi, KA Hashmi, D Stricker, MZ Afzal Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 19 | 2024 |
| Towards end-to-end semi-supervised table detection with deformable transformer T Shehzadi, K Azeem Hashmi, D Stricker, M Liwicki, M Zeshan Afzal International Conference on Document Analysis and Recognition, 51-76, 2023 | 16 | 2023 |
| Mask-aware semi-supervised object detection in floor plans T Shehzadi, KA Hashmi, A Pagani, M Liwicki, D Stricker, MZ Afzal Applied Sciences 12 (19), 9398, 2022 | 15 | 2022 |
| Continual learning for table detection in document images M Minouei, KA Hashmi, MR Soheili, MZ Afzal, D Stricker Applied Sciences 12 (18), 8969, 2022 | 14 | 2022 |
| Investigating attention mechanism for page object detection in document images S Naik, KA Hashmi, A Pagani, M Liwicki, D Stricker, MZ Afzal Applied Sciences 12 (15), 7486, 2022 | 14 | 2022 |
| Feedback learning: Automating the process of correcting and completing the extracted information KA Hashmi, RB Ponnappa, SS Bukhari, M Jenckel, A Dengel 2019 International Conference on Document Analysis and Recognition Workshops …, 2019 | 13 | 2019 |
| BoxMask: Revisiting bounding box supervision for video object detection KA Hashmi, A Pagani, D Stricker, MZ Afzal Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 12 | 2023 |
| Rethinking learnable proposals for graphical object detection in scanned document images S Sinha, KA Hashmi, A Pagani, M Liwicki, D Stricker, MZ Afzal Applied Sciences 12 (20), 10578, 2022 | 12 | 2022 |
| Bridging the performance gap between DETR and R-CNN for graphical object detection in document images T Shehzadi, KA Hashmi, D Stricker, M Liwicki, MZ Afzal arXiv preprint arXiv:2306.13526, 2023 | 9 | 2023 |
| Toward semi-supervised graphical object detection in document images G Kallempudi, KA Hashmi, A Pagani, M Liwicki, D Stricker, MZ Afzal Future Internet 14 (6), 176, 2022 | 7 | 2022 |
Didier StrickerProfessor for Computer Science, University KaiserslauternAdresă de e-mail confirmată pe dfki.uni-kl.de
