| LCU-Net: A novel low-cost U-Net for environmental microorganism image segmentation J Zhang, C Li, S Kosov, M Grzegorzek, K Shirahama, T Jiang, C Sun, Z Li, ... Pattern Recognition 115, 107885, 2021 | 157 | 2021 |
| Accurate real-time disparity estimation with variational methods S Kosov, T Thormählen, HP Seidel Advances in Visual Computing: 5th International Symposium, ISVC 2009, Las …, 2009 | 96 | 2009 |
| Environmental microorganism classification using conditional random fields and deep convolutional neural networks S Kosov, K Shirahama, C Li, M Grzegorzek Pattern recognition 77, 248-261, 2018 | 82 | 2018 |
| A new pairwise deep learning feature for environmental microorganism image analysis F Kulwa, C Li, J Zhang, K Shirahama, S Kosov, X Zhao, T Jiang, ... Environmental Science and Pollution Research 29 (34), 51909-51926, 2022 | 35 | 2022 |
| Rapid stereo-vision enhanced face detection S Kosov, K Scherbaum, K Faber, T Thormählen, HP Seidel 2009 16th IEEE International Conference on Image Processing (ICIP), 1221-1224, 2009 | 26 | 2009 |
| Rapid stereo-vision enhanced face recognition S Kosov, T Thormählen, HP Seidel 2010 IEEE International Conference on Image Processing, 2437-2440, 2010 | 16 | 2010 |
| Direct Graphical Models C++ library S Kosov http://research.project-10.de/dgm/, 2013 | 15 | 2013 |
| Design of a spectral–spatial pattern recognition framework for risk assessments using Landsat data—a case study in Chile AC Braun, C Rojas, C Echeverri, F Rottensteiner, HP Bähr, J Niemeyer, ... IEEE journal of selected topics in applied earth observations and remote …, 2014 | 14 | 2014 |
| Sequential gaussian mixture models for two-level conditional random fields S Kosov, F Rottensteiner, C Heipke German Conference on Pattern Recognition, 153-163, 2013 | 11 | 2013 |
| Segmentation of weakly visible environmental microorganism images using pair-wise deep learning features F Kulwa, C Li, M Grzegorzek, MM Rahaman, K Shirahama, S Kosov Biomedical Signal Processing and Control 79, 104168, 2023 | 9 | 2023 |
| Multi–View 3D Reconstruction with Variational Method S Kosov Saarland University, 2008 | 5 | 2008 |
| A two-layer conditional random field for the classification of partially occluded objects S Kosov, P Kohli, F Rottensteiner, C Heipke arXiv preprint arXiv:1307.3043, 2013 | 4 | 2013 |
| 3D map reconstruction with variational methods S Kosov Master thesis, Saarland University, 2008 | 4 | 2008 |
| Multi-layer conditional random fields for revealing unobserved entities S Kosov | 3 | 2018 |
| Using active illumination for accurate variational space-time stereo S Kosov, T Thormählen, HP Seidel Image Analysis: 17th Scandinavian Conference, SCIA 2011, Ystad, Sweden, May …, 2011 | 3 | 2011 |
| Labeling of partially occluded regions via the multi-layer crf S Kosov, K Shirahama, M Grzegorzek Multimedia Tools and Applications 78 (2), 2551-2569, 2019 | 2 | 2019 |
| 3D classification of crossroads from multiple aerial images using conditional random fields S Kosov, F Rottensteiner, C Heipke 7th IAPR Workshop on Pattern Recognition in Remote Sensing (PRRS), 1-4, 2012 | 2 | 2012 |
| Die getaktete Gruppenstrahlertechnik und ihre Anwendungen A BULAVINOV, S KOSOV, M KRÖNING, R PINCHUK, S PUDOVIKOV, ... Seminar „Moderne Systemtechnik bei Prüfungen mit Ultraschall “des …, 2007 | 2 | 2007 |
| FlexRay communication protocol S Kosov (Wake Up and Start Up), 0 | 1 | |
Kimiaki ShirahamaDoshisha UniversityVerified email at mail.doshisha.ac.jp
