Dr. rer. nat. Sven Sickert
Sven Sickert
Address:Computer Vision Group
Department of Mathematics and Computer Science
Friedrich Schiller University of Jena
Ernst-Abbe-Platz 2
07743 Jena
Germany
Phone:+49 (0) 3641 9 46424
E-mail:sven (dot) sickert (at) uni-jena (dot) de
Room:1211
Links:Twitter, GoogleScholar
Curriculum Vitae
 since 2019 Team Leader: “Learning from 3D and Unstructured Data”
Computer Vision Group, Friedrich Schiller University Jena
 since 2019
 Lecturer & Study Program Coordinator for Computer Science studies
Institute for Computer Science Jena, Friedrich Schiller University Jena
 Apr 2013 to Dec 2018
 Research Associate / PhD Student
Computer Vision Group, Friedrich Schiller University Jena
PhD Thesis: “Semantic Segmentation of 3D Data using Contextual Cues”
 Oct 2007 to Dec 2012 Studies in Computer Science (Diploma)
Friedrich Schiller University Jena
Focus: Digital Image Processing / Computer Vision
Diploma Thesis: “Strategien des Aktiven Lernenes” (“Strategies in Active Learning”)
Research Interests
  • 3D Point Cloud Analysis
  • Representation Learning
  • Semantic Segmentation
  • Medical Image Understanding
Projects
Ongoing
Former
Reviewer Activities
  • IEEE Transactions on Image Processing (TIP, since 2020)
  • UK Conference on Medical Image Understanding and Analysis (MIUA, 2020)
  • Expert Systems With Applications (2019)
  • Special Session on Machine Learning in Advanced Machine Vision (AMV) at ICMLA 2019
Teaching
Summer term 2022
Winter term 2021/2022
  • Grundlagen informatischer Problemlösung (Grundlagen der Programmierung) with Prof. Wolfram Amme and André Schäfer
  • Fortgeschrittenes Programmierpraktikum with Prof. Wolfram Amme
  • Systemsoftware with Markus Fleischauer and Matthias Mitterreiter
  • Grundlagen der Programmierung mit Python (Teil 2) with Prof. Martin Mundhenk
  • Informatik für Werkstoffwissenschaftler with Paul Bodesheim
Supervised Theses
  • Chima Nmerenu: “Learning Networks for 3D Point Cloud Data based on Synthetically Generated Samples from Mathematical Formulas”. Master thesis, 2021.
  • Xu Yang: “Spherical Convolutions at Anatomical Landmarks for Facial Analysis Tasks”. Master thesis, 2021. (joint supervision with Jhonatan Contreras)
  • Felix Fleisch: “3D-Momente Invarianten auf Basis gelernter Triangulierungen zur semantischen Analyse von 3D-Punktwolken”. Bachelor thesis, 2021.
  • Selina Müller: “Integrating Hierarchical Knowledge for Medical Image Analysis Tasks”. Master thesis, 2019. (joint supervision with Clemens-Alexander Brust)
  • David Pertzborn: “Application and Analysis of Generative Adversarial Network for Non-Supervised Anomaly Detection in Colonoscopy Imaging”. Master thesis, 2019. (joint supervision with Clemens-Alexander Brust and Christoph Theiß)
  • Marie Arlt: “Improving Semantic Segmentation of Polyps in Coloscopic Data using Augmentation Techniques”. Master thesis, 2019. (joint supervision with Clemens-Alexander Brust and Christoph Theiß)
  • Martin Nußbaum: “Semantische Segmentierung von sequenziellen Bilddaten mittels Rekurrenter Neuronaler Netze”. Bachelor thesis, 2017.
  • Christopher Manthey: “Fahrbahnsegmentierung mittels echtzeitfähiger Convolutional Networks in eingebetteten Systemen”. Master thesis, 2016.
  • Matthias Reuse: “Analyse verschiedener Demosaicing-Verfahren für Aufgaben der Fahrbahnerkennung”. Bachelor thesis, 2016. (joint supervision with Manuel Amthor)
  • Christoph Runge: “Semantische Segmentierung mittels Iterative Context Forests für große Mehrklassenprobleme”. Bachelor thesis, 2015.
  • Clemens-Alexander Brust: “Semantische Segmentierung mittels Convolutional Networks für die automatische Fahrbahnsegmentierung” Bachelor thesis, 2014. (joint supervision with Marcel Simon and Erik Rodner)

If you are interested in doing a Bachelor’s or Master’s thesis in the area of computer vision, you are very welcome to contact me!

Publications
2022
Metaphor Detection for Low Resource Languages: From Zero-Shot to Few-Shot Learning in Middle High German
Felix Schneider and Sven Sickert and Phillip Brandes and Sophie Marshall and Joachim Denzler.
LREC Workshop on Multiword Expression (LREC-WS). Pages 75-80. 2022.
[bibtex] [web] [code] [abstract]
Automatic Objective Severity Grading of Peripheral Facial Palsy Using 3D Radial Curves Extracted from Point Clouds
Tim Büchner and Sven Sickert and Gerd F. Volk and Orlando Guntinas-Lichius and Joachim Denzler.
Challenges of Trustable AI and Added-Value on Health. Pages 179-183. 2022.
[bibtex] [web] [code] [abstract]
2021
Facial Behavior Analysis using 4D Curvature Statistics for Presentation Attack Detection
Martin Thümmel and Sven Sickert and Joachim Denzler.
IEEE International Workshop on Biometrics and Forensics (IWBF). Pages 1-6. 2021.
[bibtex] [web] [code] [abstract]
2020
Automatic and Objective Facial Palsy Grading Index Prediction using Deep Feature Regression
Anish Raj and Oliver Mothes and Sven Sickert and Gerd F. Volk and Orlando Guntinas-Lichius and Joachim Denzler.
Annual Conference on Medical Image Understanding and Analysis (MIUA). Pages 253-266. 2020.
[bibtex] [web] [abstract]
Region-based Edge Convolutions with Geometric Attributes for the Semantic Segmentation of Large-scale 3D Point Clouds
Jhonatan Contreras and Sven Sickert and Joachim Denzler.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13 (1) : pp. 2598-2609. 2020.
[bibtex] [pdf] [web] [abstract]
2019
Intraoperative Online Image-guided Biopsie on the Basis of a Deep Learning Algorithm to the Automatic Detection of Head and Neck Carcinoma by Means of Real Time Near-Infrared ICG Fluorescence Endoscopy
Andreas Dittberner and Sven Sickert and Joachim Denzler and Orlando Guntinas-Lichius.
Laryngo-Rhino-Otologie. 98 (S02) : pp. 115. 2019.
[bibtex] [web]
Automatically Estimating Forestal Characteristics in 3D Point Clouds using Deep Learning
Jhonatan Contreras and Sven Sickert and Joachim Denzler.
iDiv Annual Conference 2019. 2019. Poster
[bibtex] [web] [abstract]
Automated Polyp Differentiation on Coloscopic Data using Semantic Segmentation with CNNs
Marie Arlt and Jack Peter and Sven Sickert and Clemens-Alexander Brust and Joachim Denzler and Andreas Stallmach.
Endoscopy. 51 (04) : pp. 4. 2019.
[bibtex] [web] [abstract]
2018
Development of an Automatic Image Analysis Method by Deep Learning Methods for the Detection of Head and Neck Cancer Based on Standard Real-Time Near-Infrared ICG Fluorescence Endoscopy Images (NIR-ICG-FE)
Andreas Dittberner and Sven Sickert and Joachim Denzler and Orlando Guntinas-Lichius and Thomas Bitter and Sven Koscielny.
Laryngo-Rhino-Otologie. 97 (S02) : pp. 97. 2018.
[bibtex] [web] [abstract]
Automated MRI Volumetry of the Olfactory Bulb
Niclas Schmitt and Sven Sickert and Orlando Guntinas-Lichius and Thomas Bitter and Joachim Denzler.
Laryngo-Rhino-Otologie. 97 (S02) : pp. 36. 2018.
[bibtex] [web] [abstract]
2017
Predicting Carbon Dioxide and Energy Fluxes with Empirical Approaches in FLUXNET
Gianluca Tramontana and Martin Jung and Christopher R. Schwalm and Kazuhito Ichii and Gustau Camps-Valls and Botond Raduly and Markus Reichstein and M. Altaf Arain and Alessandro Cescatti and Gerard Kiely and Lutz Merbold and Penelope Serrano-Ortiz and Sven Sickert and Sebastian Wolf and Dario Papale.
European Geosciences Union General Assembly (EGU): Abstract + Poster Presentation. 2017.
[bibtex] [pdf] [web]
Semantic Segmentation of Outdoor Areas using 3D Moment Invariants and Contextual Cues
Sven Sickert and Joachim Denzler.
German Conference on Pattern Recognition (GCPR). Pages 165-176. 2017.
[bibtex] [pdf] [abstract]
2016
Neither Quick Nor Proper -- Evaluation of QuickProp for Learning Deep Neural Networks
Clemens-Alexander Brust and Sven Sickert and Marcel Simon and Erik Rodner and Joachim Denzler. 2016. Technical Report TR-FSU-INF-CV-2016-01
[bibtex] [pdf] [abstract]
Predicting Carbon Dioxide and Energy Fluxes Across Global FLUXNET Sites with Regression Algorithms
Gianluca Tramontana and Martin Jung and Christopher R. Schwalm and Kazuhito Ichii and Gustau Camps-Valls and Botond Raduly and Markus Reichstein and M. Altaf Arain and Alessandro Cescatti and Gerard Kiely and Lutz Merbold and Penelope Serrano-Ortiz and Sven Sickert and Sebastian Wolf and and Dario Papale.
Biogeosciences. 13 (14) : pp. 4291-4313. 2016.
[bibtex] [web] [abstract]
Semantic Volume Segmentation with Iterative Context Integration for Bio-medical Image Stacks
Sven Sickert and Erik Rodner and Joachim Denzler.
Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications (PRIA). 26 (1) : pp. 197-204. 2016.
[bibtex] [pdf] [abstract]
2015
Convolutional Patch Networks with Spatial Prior for Road Detection and Urban Scene Understanding
Clemens-Alexander Brust and Sven Sickert and Marcel Simon and Erik Rodner and Joachim Denzler.
Computer Vision Theory and Applications (VISAPP). Pages 510-517. 2015.
[bibtex] [pdf] [abstract]
Efficient Convolutional Patch Networks for Scene Understanding
Clemens-Alexander Brust and Sven Sickert and Marcel Simon and Erik Rodner and Joachim Denzler. 2015. Poster presentation and extended abstract
[bibtex] [pdf] [abstract]
2014
An ensemble of global high-resolution products of energy fluxes over land
Martin Jung and Kazuhito Ichii and Gustau Camps-Valls and Dario Papale and Gianluca Tramontana and Sven Sickert and Christopher Schwalm and Markus Reichstein.
International Scientific Conference on the Global Water and Energy Cycle (GEWEX). 2014. Poster
[bibtex] [abstract]
Semantic Volume Segmentation with Iterative Context Integration
Sven Sickert and Erik Rodner and Joachim Denzler.
Open German-Russian Workshop on Pattern Recognition and Image Understanding (OGRW). Pages 220-225. 2014.
[bibtex] [pdf] [web] [abstract]