default search action
Jens Rittscher
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [c85]Ruby Wood, Enric Domingo, Viktor Hendrik Koelzer, Timothy S. Maughan, Jens Rittscher:
Cluster Triplet Loss for Unsupervised Domain Adaptation on Histology Images. CVPR Workshops 2024: 5122-5131 - [c84]Alexander Sauer, Yuan Tian, Joerg Bewersdorf, Jens Rittscher:
Refining Biologically Inconsistent Segmentation Masks with Masked Autoencoders. CVPR Workshops 2024: 6904-6912 - [c83]George Batchkala, Bin Li, Mengran Fan, Mark McCole, Cecilia Brambilla, Fergus Gleeson, Jens Rittscher:
Accurate Subtyping of Lung Cancers by Modelling Class Dependencies. ISBI 2024: 1-5 - [c82]Shangqi Gao, Lisa Browning, Nasullah Khalid Alham, Andrew Protheroe, Keir Edwards, Josh Hamblin, Jens Rittscher, Clare Verrill:
Characterising borderline areas in bladder tumour grading with Bayesian graph neural networks. ISBI 2024: 1-5 - [c81]George Batchkala, Bin Li, Jens Rittscher:
Evaluating Histopathology Foundation Models for Few-Shot Tissue Clustering: An Application to LC25000 Augmented Dataset Cleaning. DEMI@MICCAI 2024: 11-21 - [c80]Louis-Oscar Morel, Muhammad Muzammel, Nathan Vinçon, Valentin Derangère, Sylvain Ladoire, Jens Rittscher:
MultiVarNet - Predicting Tumour Mutational Status at the Protein Level. MICCAI (3) 2024: 314-324 - [i25]Ziang Xu, Jens Rittscher, Sharib Ali:
SSTFB: Leveraging self-supervised pretext learning and temporal self-attention with feature branching for real-time video polyp segmentation. CoRR abs/2406.10200 (2024) - 2023
- [j13]Nikhil Kumar Tomar, Debesh Jha
, Michael A. Riegler
FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation. IEEE Trans. Neural Networks Learn. Syst. 34(11): 9375-9388 (2023) - [c79]Alexander Sauer, Mariia Dmitrieva, Hongqing Han, Jens Rittscher:
Leveraging Inter-Annotator Disagreement for Semi-Supervised Segmentation. ISBI 2023: 1-5 - [c78]Ruby Wood
Joint Prediction of Response to Therapy, Molecular Traits, and Spatial Organisation in Colorectal Cancer Biopsies. MICCAI (5) 2023: 758-767 - [i24]Ziang Xu, Jens Rittscher, Sharib Ali:
SSL-CPCD: Self-supervised learning with composite pretext-class discrimination for improved generalisability in endoscopic image analysis. CoRR abs/2306.00197 (2023) - [i23]Willem Bonnaffé, CRUK ICGC Prostate Group, Freddie Hamdy, Yang Hu, Ian Mills, Jens Rittscher, Clare Verrill, Dan J. Woodcock:
Beyond attention: deriving biologically interpretable insights from weakly-supervised multiple-instance learning models. CoRR abs/2309.03925 (2023) - 2022
- [j12]Soumya Gupta
Multi-class motion-based semantic segmentation for ureteroscopy and laser lithotripsy. Comput. Medical Imaging Graph. 101: 102112 (2022) - [c77]Hongqing Han
Self-Supervised Voxel-Level Representation Rediscovers Subcellular Structures in Volume Electron Microscopy. CVPR Workshops 2022: 1873-1882 - [c76]Natalia Garcia Martin
A Graph Based Neural Network Approach to Immune Profiling of Multiplexed Tissue Samples. EMBC 2022: 3063-3067 - [c75]Helen Theissen, Tapabrata Chakraborty, Stefano Malacrino, Daniel Royston
Multi-Scale Graphical Representation of Cell Environment. EMBC 2022: 3522-3525 - [c74]Ziang Xu, Sharib Ali
Additive Angular Margin Loss and Model Scaling Network for Optimised Colitis Scoring. ISBI 2022: 1-5 - [c73]Ziang Xu
Self-supervised Approach for a Fully Assistive Esophageal Surveillance: Quality, Anatomy and Neoplasia Guidance. CaPTion@MICCAI 2022: 14-23 - [c72]Kristofer E. delas Peñas, Ralf Haeusler, Sally Feng
Profiling DNA Damage in 3D Histology Samples. MOVI@MICCAI 2022: 84-93 - [c71]Ziang Xu
Patch-Level Instance-Group Discrimination with Pretext-Invariant Learning for Colitis Scoring. MLMI@MICCAI 2022: 101-110 - [c70]George Batchkala
Active Data Enrichment by Learning What to Annotate in Digital Pathology. CaPTion@MICCAI 2022: 118-127 - [c69]Yang Hu, Korsuk Sirinukunwattana, Kezia Gaitskell, Ruby Wood, Clare Verrill, Jens Rittscher:
Predicting Molecular Traits from Tissue Morphology Through Self-interactive Multi-instance Learning. MICCAI (2) 2022: 130-139 - [c68]Ruby Wood
Enhancing Local Context of Histology Features in Vision Transformers. AIIIMA/MIABID@MICCAI 2022: 154-163 - [c67]Soumya Gupta
UNet-eVAE: Iterative Refinement Using VAE Embodied Learning for Endoscopic Image Segmentation. MLMI@MICCAI 2022: 161-170 - [i22]Natalia Garcia Martin, Stefano Malacrino, Marta Wojciechowska, Leticia Campo, Helen Jones, David C. Wedge, Chris Holmes, Korsuk Sirinukunwattana, Heba Sailem, Clare Verrill, Jens Rittscher:
A Graph Based Neural Network Approach to Immune Profiling of Multiplexed Tissue Samples. CoRR abs/2202.00813 (2022) - [i21]Sharib Ali, Noha M. Ghatwary, Debesh Jha, Ece Isik-Polat, Gorkem Polat, Chen Yang, Wuyang Li, Adrian Galdran, Miguel Ángel González Ballester, Vajira Thambawita, Steven Hicks, Sahadev Poudel, Sang-Woong Lee, Ziyi Jin, Tianyuan Gan, ChengHui Yu, Jiangpeng Yan, Doyeob Yeo, Hyunseok Lee, Nikhil Kumar Tomar, Mahmood Haithami, Amr Ahmed, Michael A. Riegler, Christian Daul, Pål Halvorsen, Jens Rittscher, Osama E. Salem, Dominique Lamarque, Renato Cannizzaro, Stefano Realdon, Thomas de Lange, James E. East:
Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge. CoRR abs/2202.12031 (2022) - [i20]Ziang Xu, Sharib Ali
Patch-level instance-group discrimination with pretext-invariant learning for colitis scoring. CoRR abs/2207.05192 (2022) - 2021
- [j11]Debesh Jha
Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning. IEEE Access 9: 40496-40510 (2021) - [j10]Sharib Ali
A deep learning framework for quality assessment and restoration in video endoscopy. Medical Image Anal. 68: 101900 (2021) - [j9]Sharib Ali
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy. Medical Image Anal. 70: 102002 (2021) - [c66]Sebastian Elmes, Tapabrata Chakraborti, Mengran Fan, Holm H. Uhlig, Jens Rittscher:
Automated Annotator: Capturing Expert Knowledge for Free. EMBC 2021: 2664-2667 - [c65]Helen Theissen, Tapabrata Chakraborti, Stefano Malacrino, Korsuk Sirinukunwattana, Daniel Royston
Learning Cellular Phenotypes through Supervision. EMBC 2021: 3592-3595 - [c64]Tapabrata Chakraborti, Fergus Gleeson, Jens Rittscher:
Contrastive Representations for Continual Learning of Fine-Grained Histology Images. MLMI@MICCAI 2021: 1-9 - [c63]Marta Wojciechowska
Early Detection of Liver Fibrosis Using Graph Convolutional Networks. MICCAI (8) 2021: 217-226 - [c62]Numan Celik
EndoUDA: A Modality Independent Segmentation Approach for Endoscopy Imaging. MICCAI (3) 2021: 303-312 - [c61]Tamal Chowdhury, Angad R. S. Bajwa, Tapabrata Chakraborti, Jens Rittscher, Umapada Pal:
Exploring the Correlation Between Deep Learned and Clinical Features in Melanoma Detection. MIUA 2021: 3-17 - [c60]Ziang Xu, Sharib Ali
Improved Artifact Detection in Endoscopy Imaging Through Profile Pruning. MIUA 2021: 87-97 - [i19]Nikhil Kumar Tomar, Debesh Jha, Michael A. Riegler, Håvard D. Johansen, Dag Johansen, Jens Rittscher, Pål Halvorsen, Sharib Ali:
FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation. CoRR abs/2103.17235 (2021) - [i18]Soumya Gupta
Multi-class motion-based semantic segmentation for ureteroscopy and laser lithotripsy. CoRR abs/2104.01268 (2021) - [i17]Sharib Ali, Debesh Jha, Noha M. Ghatwary, Stefano Realdon, Renato Cannizzaro, Osama E. Salem, Dominique Lamarque, Christian Daul, Kim V. Anonsen, Michael A. Riegler, Pål Halvorsen, Jens Rittscher, Thomas de Lange, James E. East:
PolypGen: A multi-center polyp detection and segmentation dataset for generalisability assessment. CoRR abs/2106.04463 (2021) - [i16]Numan Celik, Sharib Ali, Soumya Gupta, Barbara Braden, Jens Rittscher:
EndoUDA: A modality independent segmentation approach for endoscopy imaging. CoRR abs/2107.05342 (2021) - [i15]Francesco Reina
TRAIT2D: a Software for Quantitative Analysis of Single Particle Diffusion Data. F1000Research 10: 838 (2021) - 2020
- [c59]Mengran Fan, Tapabrata Chakraborti, Eric I-Chao Chang, Yan Xu
Fine-Grained Multi-Instance Classification in Microscopy Through Deep Attention. ISBI 2020: 169-173 - [c58]Soumya Gupta
MI-UNet: Improved Segmentation in Ureteroscopy. ISBI 2020: 212-216 - [c57]Mariia Dmitrieva, Joël Lefebvre, Kristofer delas Peñas, Helen L. Zenner, Jennifer Richens, Daniel St Johnston, Jens Rittscher:
Short Trajectory Segmentation with 1D UNET Framework: Application to Secretory Vesicle Dynamics. ISBI 2020: 891-894 - [c56]Joël Lefebvre, Avelino Javer, Mariia Dmitrieva, Jens Rittscher, Bohdan Lewków, Edward Allgeyer, George Sirinakis, Daniel St Johnston:
Single-Molecule Localization Microscopy Reconstruction Using Noise2Noise for Super-Resolution Imaging of Actin Filaments. ISBI 2020: 1596-1599 - [c55]Kristofer delas Peñas, Mariia Dmitrieva, Joël Lefebvre, Helen L. Zenner, Edward Allgeyer, Martin Booth, Daniel St Johnston, Jens Rittscher:
Extracting Axial Depth and Trajectory Trend Using Astigmatism, Gaussian Fitting, and CNNs for Protein Tracking. ISBI 2020: 1634-1637 - [c54]Ka Ho Tam, Korsuk Sirinukunwattana, Maria F. Soares, Maria Kaisar, Rutger Ploeg, Jens Rittscher:
Improving Pathological Distribution Measurements with Bayesian Uncertainty. UNSURE/GRAIL@MICCAI 2020: 61-70 - [c53]Mengran Fan, Tapabrata Chakraborti, Eric I-Chao Chang, Yan Xu
Microscopic Fine-Grained Instance Classification Through Deep Attention. MICCAI (5) 2020: 490-499 - [c52]Sharib Ali
Additive Angular Margin for Few Shot Learning to Classify Clinical Endoscopy Images. MLMI@MICCAI 2020: 494-503 - [c51]Soumya Gupta
Motion induced segmentation of stone fragments in ureteroscopy video. Medical Imaging: Image-Guided Procedures 2020: 1131514 - [c50]Andrew Torr, Berke Doga Basaran
DeepSplit: Segmentation of Microscopy Images Using Multi-task Convolutional Networks. MIUA 2020: 155-167 - [e1]Sharib Ali, Christian Daul, Jens Rittscher, Danail Stoyanov, Enrico Grisan:
Proceedings of the 2nd International Workshop and Challenge on Computer Vision in Endoscopy, EndoCV@ISBI 2020, Iowa City, Iowa, USA, 3rd April 2020. CEUR Workshop Proceedings 2595, CEUR-WS.org 2020 [contents] - [i14]Sharib Ali, Noha M. Ghatwary, Barbara Braden, Dominique Lamarque, Adam Bailey, Stefano Realdon, Renato Cannizzaro, Jens Rittscher, Christian Daul, James E. East:
Endoscopy disease detection challenge 2020. CoRR abs/2003.03376 (2020) - [i13]Sharib Ali, Binod Bhattarai, Tae-Kyun Kim, Jens Rittscher:
Additive Angular Margin for Few Shot Learning to Classify Clinical Endoscopy Images. CoRR abs/2003.10033 (2020) - [i12]Mengran Fan, Tapabrata Chakraborti, Eric I-Chao Chang, Yan Xu, Jens Rittscher:
Microscopic fine-grained instance classification through deep attention. CoRR abs/2010.02818 (2020) - [i11]Sharib Ali, Mariia Dmitrieva, Noha M. Ghatwary, Sophia Bano, Gorkem Polat, Alptekin Temizel, Adrian Krenzer, Amar Hekalo, Yun Bo Guo, Bogdan J. Matuszewski, Mourad Gridach, Irina Voiculescu, Vishnusai Yoganand, Arnav Chavan, Aryan Raj, Nhan T. Nguyen, Dat Q. Tran, Lê Duy Huynh, Nicolas Boutry, Shahadate Rezvy, Haijian Chen, Yoon Ho Choi, Anand Subramanian, Velmurugan Balasubramanian, Xiaohong W. Gao, Hongyu Hu, Yusheng Liao, Danail Stoyanov, Christian Daul, Stefano Realdon, Renato Cannizzaro, Dominique Lamarque, Terry Tran-Nguyen, Adam Bailey, Barbara Braden, James E. East, Jens Rittscher:
A translational pathway of deep learning methods in GastroIntestinal Endoscopy. CoRR abs/2010.06034 (2020) - [i10]Debesh Jha, Sharib Ali, Håvard D. Johansen, Dag Johansen, Jens Rittscher, Michael A. Riegler, Pål Halvorsen:
Real-Time Polyp Detection, Localisation and Segmentation in Colonoscopy Using Deep Learning. CoRR abs/2011.07631 (2020) - [i9]Numan Celik, Soumya Gupta
Unsupervised Adversarial Domain Adaptation For Barrett's Segmentation. CoRR abs/2012.05316 (2020)
2010 – 2019
- 2019
- [j8]Sundaresan Raman, Shantanu Singh, Thierry Pécot
Capturing variations in nuclear phenotypes. J. Comput. Sci. 36 (2019) - [c49]Sharib Ali
Efficient Video Indexing for Monitoring Disease Activity and Progression in the Upper Gastrointestinal Tract. ISBI 2019: 91-95 - [c48]Sharib Ali
Ink Removal from Histopathology Whole Slide Images by Combining Classification, Detection and Image Generation Models. ISBI 2019: 928-932 - [c47]Andrea Chatrian, Korsuk Sirinukunwattana, Clare Verrill, Jens Rittscher
Towards the Identification of Histology Based Subtypes in Prostate Cancer. ISBI 2019: 948-952 - [c46]Sharib Ali
Conv2Warp: An Unsupervised Deformable Image Registration with Continuous Convolution and Warping. MLMI@MICCAI 2019: 489-497 - [c45]Avelino Javer, Jens Rittscher
Semantic Filtering Through Deep Source Separation on Microscopy Images. MLMI@MICCAI 2019: 498-506 - [c44]Mariia Dmitrieva, Helen L. Zenner, Jennifer Richens, Daniel St Johnston, Jens Rittscher:
Protein Tracking By CNN-Based Candidate Pruning And Two-Step Linking With Bayesian Network. MLSP 2019: 1-6 - [i8]Sharib Ali
A deep learning framework for quality assessment and restoration in video endoscopy. CoRR abs/1904.07073 (2019) - [i7]Sharib Ali
Endoscopy artifact detection (EAD 2019) challenge dataset. CoRR abs/1905.03209 (2019) - [i6]Sharib Ali, Jens Rittscher:
Efficient video indexing for monitoring disease activity and progression in the upper gastrointestinal tract. CoRR abs/1905.04384 (2019) - [i5]Sharib Ali, Nasullah Khalid Alham, Clare Verrill, Jens Rittscher:
Ink removal from histopathology whole slide images by combining classification, detection and image generation models. CoRR abs/1905.04385 (2019) - [i4]Sharib Ali, Jens Rittscher:
Conv2Warp: An unsupervised deformable image registration with continuous convolution and warping. CoRR abs/1908.06194 (2019) - [i3]Avelino Javer, Jens Rittscher:
Semantic filtering through deep source separation on microscopy images. CoRR abs/1909.00691 (2019) - 2018
- [c43]Avelino Javer, André E. X. Brown, Iasonas Kokkinos, Jens Rittscher
Identification of C. elegans Strains Using a Fully Convolutional Neural Network on Behavioural Dynamics. ECCV Workshops (6) 2018: 455-464 - [c42]Mengran Fan, Jens Rittscher
Global probabilistic models for enhancing segmentation with convolutional networks. ISBI 2018: 1234-1238 - [c41]Korsuk Sirinukunwattana, Nasullah Khalid Alham, Clare Verrill, Jens Rittscher
Improving Whole Slide Segmentation Through Visual Context - A Systematic Study. MICCAI (2) 2018: 192-200 - [i2]Korsuk Sirinukunwattana, Nasullah Khalid Alham, Clare Verrill, Jens Rittscher:
Improving Whole Slide Segmentation Through Visual Context - A Systematic Study. CoRR abs/1806.04259 (2018) - [i1]Raghu Machiraju, Jens Rittscher, Motonori Ota:
Workshop on Patient Similitude: Combining Histopathological Images & Multiple-Scale Molecular Phenotypes (NII Shonan Meeting 2018-17). NII Shonan Meet. Rep. 2018 (2018) - 2017
- [c40]Heba Sailem
Discovery of Rare Phenotypes in Cellular Images Using Weakly Supervised Deep Learning. ICCV Workshops 2017: 49-55 - 2015
- [c39]Thomas A. Nketia, J. Alison Noble
Towards quantifying the impact of cell boundary estimation on morphometric analysis for phenotypic screening. ISBI 2015: 781-784 - [c38]Alberto Santamaría-Pang, Jens Rittscher
Cell segmentation and classification by hierarchical supervised shape ranking. ISBI 2015: 1296-1299 - 2014
- [c37]Jens Rittscher, Alberto Santamaría-Pang:
Mapping for tissue based cytometry. ISBI 2014: 278-281 - [c36]Thomas A. Nketia, Jens Rittscher, J. Alison Noble:
Utilizing Phase Retardation Features for Segmenting Cells in Phase Contrast Microscopy Images. MIUA 2014: 191-196 - 2013
- [j7]Michael J. Gerdes, Christopher J. Sevinsky, Anup Sood, Sudeshna Adak, Musodiq O. Bello, Alexander Bordwell, Ali Can, Alex Corwin, Sean Dinn, Robert Filkins, Denise Hollman, Vidya Kamath, Sireesha Kaanumalle, Kevin B. Kenny, Melinda Larsen, Michael Lazare, Qing Li, Christina Lowes, Colin C. McCulloch, Elizabeth McDonough, Michael Montalto, Zhengyu Pang, Jens Rittscher
Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue. Proc. Natl. Acad. Sci. USA 110(29): 11982-11987 (2013) - [c35]Alberto Santamaría-Pang, Yuchi Huang, Jens Rittscher
Cell segmentation and classification via unsupervised shape ranking. ISBI 2013: 406-409 - 2012
- [c34]Daniel Margolis, Alberto Santamaría-Pang, Jens Rittscher
Tissue segmentation and classification using graph-based unsupervised clustering. ISBI 2012: 162-165 - [c33]Xiaofeng Liu, Satish G. Iyengar, Jens Rittscher
Monitoring cardiomyocyte motionin real time through image registration and time series analysis. ISBI 2012: 1308-1311 - 2011
- [j6]Gianfranco Doretto, Thomas Sebastian, Peter H. Tu, Jens Rittscher
Appearance-based person reidentification in camera networks: problem overview and current approaches. J. Ambient Intell. Humaniz. Comput. 2(2): 127-151 (2011) - [j5]Dirk Ryan Padfield, Jens Rittscher
Coupled minimum-cost flow cell tracking for high-throughput quantitative analysis. Medical Image Anal. 15(4): 650-668 (2011) - [c32]Jilin Tu, Brandon Laflen, Xiaoming Liu, Musodiq O. Bello, Jens Rittscher
LPSM: Fitting shape model by linear programming. FG 2011: 252-258 - [c31]Shantanu Singh, Firdaus Janoos, Thierry Pécot
Identifying Nuclear Phenotypes Using Semi-supervised Metric Learning. IPMI 2011: 398-410 - [c30]Jens Rittscher
Methods and algorithms for extracting high-content signatures from cells, tissues, and model organisms. ISBI 2011: 1712-1716 - [c29]Dirk Ryan Padfield, Jens Rittscher
Quantitative biological studies enabled by robust cell tracking. ISBI 2011: 1929-1934 - [c28]Ser-Nam Lim, Gianfranco Doretto, Jens Rittscher
Multi-class Object Layout with Unsupervised Image Classification and Object Localization. ISVC (1) 2011: 573-585 - [c27]Shantanu Singh, Firdaus Janoos, Thierry Pécot
Non-parametric Population Analysis of Cellular Phenotypes. MICCAI (2) 2011: 343-351 - 2010
- [c26]Shantanu Singh, Sundaresan Raman, Enrico Caserta, Gustavo Leone, Michael C. Ostrowski
Analysis of spatial variation of nuclear morphology in tissue microenvironments. ISBI 2010: 1293-1296 - [c25]Dashan Gao, Dirk Ryan Padfield, Jens Rittscher
Automated Training Data Generation for Microscopy Focus Classification. MICCAI (2) 2010: 446-453
2000 – 2009
- 2009
- [j4]Dirk Ryan Padfield, Jens Rittscher
Spatio-temporal cell cycle phase analysis using level sets and fast marching methods. Medical Image Anal. 13(1): 143-155 (2009) - [c24]Seon Joo Kim, Gianfranco Doretto, Jens Rittscher
A model change detection approach to dynamic scene modeling. AVSS 2009: 490-495 - [c23]Dirk Ryan Padfield, Jens Rittscher
Coupled Minimum-Cost Flow Cell Tracking. IPMI 2009: 374-385 - 2008
- [c22]Dirk Ryan Padfield, Jens Rittscher
Methods for monitoring cellular motion and function. ACSCC 2008: 47-50 - [c21]Peter H. Tu, Thomas Sebastian, Gianfranco Doretto, Nils Krahnstoever, Jens Rittscher, Ting Yu:
Unified Crowd Segmentation. ECCV (4) 2008: 691-704 - [c20]Dirk Ryan Padfield, Jens Rittscher
Spatio-temporal cell segmentation and tracking for automated screening. ISBI 2008: 376-379 - 2007
- [c19]Peter H. Tu, Nils Krahnstoever, Jens Rittscher
View adaptive detection and distributed site wide tracking. AVSS 2007: 57-62 - [c18]Xiaogang Wang, Gianfranco Doretto, Thomas Sebastian, Jens Rittscher
Shape and Appearance Context Modeling. ICCV 2007: 1-8 - 2006
- [c17]Xiaoming Liu, Jens Rittscher
Optimal Pose for Face Recognition. CVPR (2) 2006: 1439-1446 - [c16]Thomas Sebastian, Jens Rittscher, Liming Yu:
Computing phagocytosis index for high-throughput applications. ISBI 2006: 546-549 - [c15]Dirk Ryan Padfield, Jens Rittscher, Thomas Sebastian, Nick Thomas, Badrinath Roysam:
Spatio-temporal cell cycle analysis using 3D level set segmentation of unstained nuclei in line scan confocal fluorescence images. ISBI 2006: 1036-1039 - 2005
- [c14]Xiaoming Liu, Peter Henry Tu, Jens Rittscher
Detecting and counting people in surveillance applications. AVSS 2005: 306-311 - [c13]Jens Rittscher
Simultaneous Estimation of Segmentation and Shape. CVPR (2) 2005: 486-493 - [c12]Jens Rittscher
Multi-Target Tracking Using Hybrid Particle Filtering. WACV/MOTION 2005: 447-454 - [c11]Nils Krahnstoever, Jens Rittscher
Activity Recognition using Visual Tracking and RFID. WACV/MOTION 2005: 494-500 - 2004
- [b1]Jens Rittscher:
Strategieflexible Entscheidungsunterstützung in der Ablaufplanung für Produzenten. Dortmund University of Technology, 2004, ISBN 3-89957-012-X, pp. 1-171 - [c10]Peter H. Tu, Jens Rittscher:
Crowd Segmentation Through Emergent Labeling. ECCV Workshop SMVP 2004: 187-198 - 2003
- [c9]Peter H. Tu, Jens Rittscher
Site Calibration for Large Indoor Scenes. AVSS 2003: 358-363 - [c8]Anthony Hoogs, Jens Rittscher, Gees C. Stein, John Schmiederer:
Video Content Annotation Using Visual Analysis and a Large Semantic Knowledgebase. CVPR (2) 2003: 327-334 - [c7]Gees C. Stein, Jens Rittscher
Enabling video annotation using a semantic database extended with visual knowledge. ICME 2003: 161-164 - 2002
- [j3]Jens Rittscher
Towards the automatic analysis of complex human body motions. Image Vis. Comput. 20(12): 905-916 (2002) - [j2]Jien Kato, Toyohide Watanabe, Sébastien Joga, Jens Rittscher
An HMM-Based Segmentation Method for Traffic Monitoring Movies. IEEE Trans. Pattern Anal. Mach. Intell. 24(9): 1291-1296 (2002) - 2001
- [c6]Josephine Sullivan, Jens Rittscher:
Guiding Random Particles by Deterministic Search. ICCV 2001: 323-330 - 2000
- [j1]Ben North, Andrew Blake, Michael Isard, Jens Rittscher
Learning and Classification of Complex Dynamics. IEEE Trans. Pattern Anal. Mach. Intell. 22(9): 1016-1034 (2000) - [c5]Josephine Sullivan, Andrew Blake, Jens Rittscher:
Statistical Foreground Modelling for Object Localisation. ECCV (2) 2000: 307-323 - [c4]Jens Rittscher, Jien Kato, Sébastien Joga, Andrew Blake:
A Probabilistic Background Model for Tracking. ECCV (2) 2000: 336-350 - [c3]Jens Rittscher, Josephine Sullivan:
An Integral Criterion for Detecting Boundary Edges and Textured Regions. ICPR 2000: 7076-7079 - [c2]Ulrich Jessen, Jens Rittscher, Ingo Scholz, Sigrid Wenzel:
Schichtenmodell für die verteilte Nutzung modellgestützter Verfahren. SimVis 2000: 17-30
1990 – 1999
- 1999
- [c1]Jens Rittscher, Andrew Blake:
Classification of Human Body Motion. ICCV 1999: 634-639
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-04 21:39 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: