| EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification P Helber, B Bischke, A Dengel, D Borth IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2019 | 3011 | 2019 |
| YFCC100M: The New Data in Multimedia Research B Thomee, B Elizalde, DA Shamma, K Ni, G Friedland, D Poland, D Borth, ... Communications of the ACM 59 (2), 64-73, 2016 | 2496 | 2016 |
| Large-scale Visual Sentiment Ontology and Detectors using Adjective Noun Pairs D Borth, R Ji, T Chen, T Breuel, SF Chang ACM International Conference on Multimedia, 223-232, 2013 | 1020 | 2013 |
| DeepSentibank: Visual Sentiment Concept Classification with Deep Convolutional Neural Networks T Chen, D Borth, T Darrell, SF Chang arXiv preprint arXiv:1410.8586, 2014 | 533 | 2014 |
| Self-Supervised Vision Transformers for Land-Cover Segmentation and Classification L Scheibenreif, J Hanna, M Mommert, D Borth Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 417 | 2022 |
| Sonyc: A system for monitoring, analyzing, and mitigating urban noise pollution JP Bello, C Silva, O Nov, RL Dubois, A Arora, J Salamon, C Mydlarz, ... Communications of the ACM 62 (2), 68-77, 2019 | 386 | 2019 |
| The New Data and New Challenges in Multimedia Research B Thomee, DA Shamma, G Friedland, B Elizalde, K Ni, D Poland, D Borth, ... arXiv preprint arXiv:1503.01817, 2015 | 356 | 2015 |
| Multi-task Learning for Segmentation of Building Footprints with Deep Neural Networks B Bischke, P Helber, J Folz, D Borth, A Dengel 2019 IEEE International Conference on Image Processing (ICIP), 1480-1484, 2019 | 354 | 2019 |
| Introducing EuroSAT: a novel dataset and deep learning benchmark for land use and land cover classification P Helber, B Bischke, A Dengel, D Borth IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018 | 326 | 2018 |
| Contrastive Self-supervised Data Fusion for Satellite Imagery L Scheibenreif, M Mommert, D Borth ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2022 | 301 | 2022 |
| Power Plant Classification from Remote Imaging with Deep Learning M Mommert, L Scheibenreif, J Hanna, D Borth 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 6391 …, 2021 | 284 | 2021 |
| Sentibank: Large-scale Ontology and Classifiers for Detecting Sentiment and Emotions in Visual Content D Borth, T Chen, R Ji, SF Chang Proceedings of the 21st ACM international conference on Multimedia, 459-460, 2013 | 271 | 2013 |
| Detection of Anomalies in Large Scale Accounting Data using Deep Autoencoder Networks M Schreyer, T Sattarov, D Borth, A Dengel, B Reimer arXiv preprint arXiv:1709.05254, 2017 | 183 | 2017 |
| The Multimedia Satellite Task at Mediaeval 2017 B Bischke, P Helber, C Schulze, S Venkat, A Dengel, D Borth | 116 | 2017 |
| Masked Vision Transformers for Hyperspectral Image Classification L Scheibenreif, M Mommert, D Borth Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 104 | 2023 |
| Detection of Flooding Events in Social Multimedia and Satellite Imagery using Deep Neural Networks. B Bischke, P Bhardwaj, A Gautam, P Helber, D Borth, A Dengel MediaEval, 2017 | 92 | 2017 |
| Hyper-Representations: Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction K Schürholt, D Kostadinov, D Borth Neural Information Processing Systems (NeurIPS), 2021 | 75* | 2021 |
| Neural plasticity-inspired foundation model for observing the earth crossing modalities Z Xiong, Y Wang, F Zhang, AJ Stewart, J Hanna, D Borth, I Papoutsis, ... CoRR, 2024 | 74 | 2024 |
| FinDiff: Diffusion models for financial tabular data generation T Sattarov, M Schreyer, D Borth Proceedings of the Fourth ACM International Conference on AI in Finance, 64-72, 2023 | 74 | 2023 |
| Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks M Schreyer, T Sattarov, C Schulze, B Reimer, D Borth KDD 2019 Workshop on Anomaly Detection in Finance, 2019 | 72 | 2019 |
Andreas DengelProfessor of Computer Science, RPTU University Kaiserslautern-Landau & Executive Director, DFKIVerified email at dfki.de
