Bilik, S., Zemcik, T., Kratochvila, L., Ricanek, D., Richter, M., Zambanini, S., & Horak, K. (2024). Machine learning and computer vision techniques in continuous beehive monitoring applications: A survey. Computers and Electronics in Agriculture, 217, Article 108560. https://doi.org/10.1016/j.compag.2023.108560 ( reposiTUm)

Anwar, H., Anwar, S., Zambanini, S., & Porikli, F. (2021). Deep ancient Roman Republican coin classification via feature fusion and attention. Pattern Recognition, 114(107871), 107871. https://doi.org/10.1016/j.patcog.2021.107871 ( reposiTUm)

Frisky, A. Z. K., Harjoko, A., Awaludin, L., Zambanini, S., & Sablatnig, R. (2021). Investigation of Single Image Depth Prediction Under Different Lighting Conditions: A Case Study of Ancient Roman Coins. Journal on Computing and Cultural Heritage, 14(4), 1–17. https://doi.org/10.1145/3465742 ( reposiTUm)

Frisky, A. Z. K., Harjoko, A., Awaludin, L., Dharmawan, A., Augoestien, N. G., Candradewi, I., Hujja, R. M., Putranto, A., Hartono, T., Suhartono, Y., Zambanini, S., & Sablatnig, R. (2021). Registered Relief Depth (RRD) borobudur dataset for single-frame depth prediction on one-side artifacts. Data in Brief, 35(106853), 106853. https://doi.org/10.1016/j.dib.2021.106853 ( reposiTUm)

Zambanini, S., Loghin, A.-M., Pfeifer, N., Soley, E. M., & Sablatnig, R. (2020). Detection of Parking Cars in Stereo Satellite Images. Remote Sensing, 12(13), 2170. https://doi.org/10.3390/rs12132170 ( reposiTUm)

Zambanini, S. (2019). Feature-based groupwise registration of historical aerial images to present-day ortho-photo maps. Pattern Recognition, 90, 66–77. https://doi.org/10.1016/j.patcog.2019.01.024 ( reposiTUm)

Anwar, H., Zambanini, S., & Kampel, M. (2015). Coarse-grained ancient coin classification using image-based reverse side motif recognition. Machine Vision and Applications, 26(2–3), 295–304. https://doi.org/10.1007/s00138-015-0665-2 ( reposiTUm)

Anwar, H., Zambanini, S., & Kampel, M. (2015). Efficient Scale- and Rotation-Invariant Encoding of Visual Words for Image Classification. IEEE Signal Processing Letters, 22(10), 1762–1765. https://doi.org/10.1109/lsp.2015.2432851 ( reposiTUm)

Anwar, H., Zambanini, S., Kampel, M., & Vondrovec, K. (2015). Ancient Coin Classification Using Reverse Motif Recognition: Image-based classification of Roman Republican coins. IEEE Signal Processing Magazine, 32(4), 64–74. https://doi.org/10.1109/msp.2015.2409331 ( reposiTUm)

Kavelar, A., Zambanini, S., & Kampel, M. (2014). Reading the legends of Roman Republican coins. Journal on Computing and Cultural Heritage, 7(1), 1–20. https://doi.org/10.1145/2583115 ( reposiTUm)

Huber-Mörk, R., Zambanini, S., Zaharieva, M., & Kampel, M. (2011). Identification of ancient coins based on fusion of shape and local features. Machine Vision and Applications, 22(6), 983–994. https://doi.org/10.1007/s00138-010-0283-y ( reposiTUm)

Zambanini, S., Sablatnig, R., Maier, H., & Langs, G. (2010). Automatic image-based assessment of lesion development during hemangioma follow-up examinations. Artificial Intelligence in Medicine, 50(2), 83–94. https://doi.org/10.1016/j.artmed.2010.06.003 ( reposiTUm)

Burges, M., Zambanini, S., & Pirker, P. (2024). CHAI: Craters in Historical Aerial Images. In 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (pp. 8241–8250). https://doi.org/10.1109/WACV57701.2024.00807 ( reposiTUm)

Burges, M., Zambanini, S., & Sablatnig, R. (2024). Making Archives Searchable: Vision-Language Models for Classification of Historical Aerial Imagery. In GeoSearch ’24: Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data (pp. 1–8). https://doi.org/10.1145/3681769.3698578 ( reposiTUm)

Burges, M., Zambanini, S., & Sablatnig, R. (2023). Exploring Learning-Based Approaches for Bomb Crater Detection in Historical Aerial Images. In Proceedings of the OAGM Workshop 2022 (pp. 60–66). https://doi.org/10.3217/978-3-85125-954-4-09 ( reposiTUm)

Frisky, A. Z. K., Brenner, S., Zambanini, S., & Sablatnig, R. (2022). Color-Light Multi Cascade Network for Single Image Depth Prediction on One Perspective Artifact Images. In G. F. Farinella, P. Radeva, & K. Bouatouch (Eds.), Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (pp. 909–916). https://doi.org/10.5220/0010801100003124 ( reposiTUm)

Frisky, A. Z. K., Putranto, A., Zambanini, S., & Sablatnig, R. (2021). MCCNet: Multi-Color Cascade Network with Weight Transfer for Single Image Depth Prediction on Outdoor Relief Images. In Pattern Recognition. ICPR International Workshops and Challenges (pp. 263–278). https://doi.org/10.1007/978-3-030-68787-8_19 ( reposiTUm)

Brenner, S., Zambanini, S., & Sablatnig, R. (2018). Detection of Bomb Craters in WWII Aerial Images. In M. Welk, M. Urschler, & P. M. Roth (Eds.), Proceedings of the OAGM Workshop 2018 Medical Image Analysis (pp. 94–97). Verlag der Technischen Universität Graz. https://doi.org/10.3217/978-3-85125-603-1-20 ( reposiTUm)

Brenner, S., Zambanini, S., & Sablatnig, R. (2018). An Investigation of Optimal Light Source Setups for Photometric Stereo Reconstruction of Historical Coins. In S. Brenner, S. Zambanini, & R. Sablatnig (Eds.), GCH 2018 Eurographics Workshop on Graphics and Cultural Heritage (pp. 203–206). Eurographics. https://doi.org/10.2312/gch.20181362 ( reposiTUm)

Zambanini, S., & Sablatnig, R. (2017). A Hough Voting Strategy for Registering Historical Aerial Images to Present-Day Satellite Imagery. In Image Analysis and Processing - ICIAP 2017 (pp. 595–605). Springer. https://doi.org/10.1007/978-3-319-68560-1_53 ( reposiTUm)

Amor-Amoros, A., Federico, P., Miksch, S., Zambanini, S., Brenner, S., & Sablatnig, R. (2017). Visual Analytics for Multitemporal Aerial Image Georeferencing. In M. Sedlmair & C. Tominski (Eds.), Proceedings of the EuroVis Workshop on Visual Analytics (EuroVA) (pp. 55–59). The Eurographics Association. https://doi.org/10.2312/eurova.20171120 ( reposiTUm)

Brenner, S., Zambanini, S., & Sablatnig, R. (2017). Image Registration and Object Detection for Assessing Unexploded Ordnance Risks ‐ A Status Report of the DeVisOR Project. In P. M. Roth, M. Vincze, W. Kubinger, A. Müller, B. Blaschitz, & S. Štolc (Eds.), Proceedings of the OAGM & ARW Joint Workshop Vision, Automation and Robotics (pp. 109–110). Verlag der Technischen Universität Graz. https://doi.org/10.3217/978-3-85125-524-9 ( reposiTUm)

Zambanini, S., Hollaus, F., & Sablatnig, R. (2016). DeVisOR - Detection and Visualization of Unexploded Ordnance Risks. In Vision Meets Robotics, Proceedings of the ÖAGM Workshop 2016 (pp. 1–2). http://hdl.handle.net/20.500.12708/56647 ( reposiTUm)

Schurischuster, S., Zambanini, S., Kampel, M., & Lamp, B. (2016). Sensor Study for Monitoring Varroa Mites on Honey Bees (Apis mellifera). In Proc. of Visual observation and analysis of Vertebrate And Insect Behavior Workshop (VAIB 2016) (p. 4). http://hdl.handle.net/20.500.12708/56648 ( reposiTUm)

Anwar, H., Zambanini, S., & Kampel, M. (2015). Invariant Image-Based Species Classification of Butterflies and Reef Fish. In Machine Vision of Animals and their Behaviour (p. 8). http://hdl.handle.net/20.500.12708/56047 ( reposiTUm)

Zambanini, S., Kavelar, A., & Kampel, M. (2014). Classifying Ancient Coins by Local Feature Matching and Pairwise Geometric Consistency Evaluation. In 2014 22nd International Conference on Pattern Recognition. 22nd International Conference on Pattern Recognition, Stockholm, Schweden, EU. IEEE. https://doi.org/10.1109/icpr.2014.523 ( reposiTUm)

Anwar, H., Zambanini, S., & Kampel, M. (2014). A Rotation-invariant Bag of Visual Words Model for Symbols-based Ancient Coin Classification. In IEEE International Conference on Image Processing 2014 (pp. 5257–5261). IEEE. http://hdl.handle.net/20.500.12708/55262 ( reposiTUm)

Anwar, H., Zambanini, S., & Kampel, M. (2014). Encoding Spatial Arrangements of Visual Words for Rotation-Invariant Image Classification. In Pattern Recognition 36th German Conference, GCPR 2014, Münster, Germany, September 2-5, 2014, Proceedings (pp. 443–452). Lecture Note in Computer Science. https://doi.org/10.1007/978-3-319-11752-2_36 ( reposiTUm)

Zambanini, S., & Kampel, M. (2014). A Large-Scale Evaluation of Correspondence-Based Coin Classification on Roman Republican Coinage. In R. Klein & P. Santos (Eds.), GCH 2014 - Eurographics Workshop on Graphics and Cultural Heritage. Eurographics. https://doi.org/10.2312/gch.20141326 ( reposiTUm)

Hödlmoser, S., Zambanini, S., & Kampel, M. (2014). Multi-image morphing: Summarizing visual information from similar ancient coin image regions. In 2014 International Conference on Virtual Systems & Multimedia (VSMM). 20th International Conference on Virtual Systems & Multimedia, Hong Kong, Non-EU. https://doi.org/10.1109/vsmm.2014.7136662 ( reposiTUm)

Kavelar, A., Zambanini, S., & Kampel, M. (2013). Reading Ancient Coin Legends: Object Recognition vs. OCR. In Proceedings of the 37th Annual Workshop of the Austrian Association for Pattern Recognition (ÖAGM/AAPR), 2013 (p. 9). arXiv.org. http://hdl.handle.net/20.500.12708/54914 ( reposiTUm)

Kavelar, A., Zambanini, S., Kampel, M., Vondrovec, K., & Siegl, K. (2013). THE ILAC-PROJECT: SUPPORTING ANCIENT COIN CLASSIFICATION BY MEANS OF IMAGE ANALYSIS. In The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (pp. 373–378). ISPRS Archives. https://doi.org/10.5194/isprsarchives-xl-5-w2-373-2013 ( reposiTUm)

Anwar, H., Zambanini, S., & Kampel, M. (2013). A Bag of Visual Words Approach for Symbols-Based Coarse-Grained Ancient Coin Classification. In Proceedings of the 37th Annual Workshop of the Austrian Association for Pattern Recognition (ÖAGM/AAPR), 2013 (p. 8). arXiv.org. http://hdl.handle.net/20.500.12708/54915 ( reposiTUm)

Zambanini, S., & Kampel, M. (2013). A Local Image Descriptor Robust to Illumination Changes. In Image Analysis (pp. 11–21). Lecture Notes on Computer Science. https://doi.org/10.1007/978-3-642-38886-6_2 ( reposiTUm)

Zambanini, S., & Sablatnig, R. (2013). Evaluation of Low-Level Image Representations for Illumination-Insensitive Recognition of Textureless Objects. In Image Analysis and Processing – ICIAP 2013 (pp. 71–80). Lecture Notes on Computer Science. https://doi.org/10.1007/978-3-642-41181-6_8 ( reposiTUm)

Anwar, H., Zambanini, S., & Kampel, M. (2013). Supporting Ancient Coin Classification by Image-Based Reverse Side Symbol Recognition. In Computer Analysis of Images and Patterns (pp. 17–25). Lecture Notes on Computer Science. https://doi.org/10.1007/978-3-642-40246-3_3 ( reposiTUm)

Zambanini, S., Kavelar, A., & Kampel, M. (2013). Improving Ancient Roman Coin Classification by Fusing Exemplar-Based Classification and Legend Recognition. In New Trends in Image Analysis and Processing – ICIAP 2013 (pp. 149–158). Lecture Notes on Computer Science. https://doi.org/10.1007/978-3-642-41190-8_17 ( reposiTUm)

Kavelar, A., Zambanini, S., & Kampel, M. (2012). Word detection applied to images of ancient Roman coins. In 2012 18th International Conference on Virtual Systems and Multimedia. 18th International Conference on Virtual Systems and Multimedia (VSMM), 2012, Mailand, Italien, EU. IEEE. https://doi.org/10.1109/vsmm.2012.6365981 ( reposiTUm)

Zambanini, S., & Kampel, M. (2012). Using Image Analysis to Match a Coin to a Database. In Archaeology in the Digital Era Papers from the 40th Annual Conference of Computer Applications and Quantitative Methods in Archaeology (pp. 195–199). Amsterdam University Press. http://hdl.handle.net/20.500.12708/54374 ( reposiTUm)

Zambanini, S., & Kampel, M. (2012). Coarse-to-Fine Correspondence Search for Classifying Ancient Coins. In Computer Vision -- ACCV 2012 Workshops. 2nd ACCV Workshop on e-Heritage, Daejeon, Südkorea, Non-EU. http://hdl.handle.net/20.500.12708/54376 ( reposiTUm)

Lasinger, K., Baldauf, M., & Zambanini, S. (2012). Evaluating Camera-based Methods for Mobile Markerless Fingertip Detection. In Proceedings of the 2nd International Workshop on Smart Mobile Applications (p. 6). http://hdl.handle.net/20.500.12708/54375 ( reposiTUm)

Zambanini, S., & Kampel, M. (2011). Automatic Coin Classification by Image Matching. In F. Niccolucci, M. Dellepiane, S. Pena Serna, H. Rushmeier, & L. Van Gool (Eds.), VAST11: The 12th International Symposium on Virtual Reality, Archaeology and Intelligent Cultural Heritage (pp. 65–72). Eurographics Association. https://doi.org/10.2312/VAST/VAST11/065-072 ( reposiTUm)

Planinc, R., Kampel, M., & Zambanini, S. (2011). Audiovisual Assistance for the Elderly - An Overview of the FEARLESS Project. In Toward Useful Services for Elderly and People with Disabilities (pp. 225–229). Lecture Notes on Computer Science. https://doi.org/10.1007/978-3-642-21535-3_31 ( reposiTUm)

Baldauf, M., Zambanini, S., Fröhlich, P., & Reichl, P. (2011). Markerless visual fingertip detection for natural mobile device interaction. In Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services - MobileHCI ’11. 13th International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI 2011), Stockholm, Schweden, EU. ACM. https://doi.org/10.1145/2037373.2037457 ( reposiTUm)

Zambanini, S., Schlapke, M., Hödlmoser, M., & Kampel, M. (2010). 3D acquisition of historical coins and its application area in numismatics. In D. Stork, J. Coddington, & A. Bentkowska-Kafel (Eds.), Computer Vision and Image Analysis of Art. SPIE & IS&T-The Society for Imaging Science and Technology. http://hdl.handle.net/20.500.12708/53358 ( reposiTUm)

Machajdik, J., Zambanini, S., & Kampel, M. (2010). Fusion of Data from Multiple Cameras for Fall Detection. In B. Gottfried & H. Aghajan (Eds.), Proceedings of the 5th Workshop on Behaviour Monitoring and Interpretation, BMI’10, Karlsruhe, Germany, September 21, 2010 (p. 7). CEUR-WS.org. http://hdl.handle.net/20.500.12708/53369 ( reposiTUm)

Zambanini, S., Machajdik, J., & Kampel, M. (2010). Early versus Late Fusion in a Multiple Camera Network for Fall Detection. In P. Blauensteiner, M. Lettner, & J. Stöttinger (Eds.), Computer Vision in a Global Society - 34th Annual Workshop of the Austrian Association for Pattern Recognition (AAPR) and the WG Visual Computing of the Austrian Computer Society (pp. 15–22). Österreichische Computer Gesellschaft. http://hdl.handle.net/20.500.12708/53364 ( reposiTUm)

Zambanini, S., Machajdik, J., & Kampel, M. (2010). Detecting Falls at Homes Using a Network of Low-Resolution Cameras. In 10th IEEE International Conference on Information Technology and Applications in Biomedicine (p. 4). IEEE. http://hdl.handle.net/20.500.12708/53377 ( reposiTUm)

Hödlmoser, M., Zambanini, S., Schlapke, M., & Kampel, M. (2010). Evaluation of Historical 3D Coin Models. In Proceedings of the 38th Annual Conference on Computer Applications and Quantitative Methods in Archaeology, Granada, Spain, April 2010 (pp. 499–504). Archaeopress. http://hdl.handle.net/20.500.12708/53465 ( reposiTUm)

Stöttinger, J., Zambanini, S., Khan, R., & Hanbury, A. (2010). FeEval A Dataset for Evaluation of Spatio-temporal Local Features. In M. Cetin, K. Boyer, & S.-W. Lee (Eds.), 2010 20th International Conference on Pattern Recognition. IEEE. https://doi.org/10.1109/icpr.2010.128 ( reposiTUm)

Zweng, A., Zambanini, S., & Kampel, M. (2010). Introducing a Statistical Behavior Model into Camera-Based Fall Detection. In G. Bebis, R. Boyle, B. Parvin, D. Koracin, R. Chung, R. Hammound, M. Hussain, T. Kar-Han, R. Crawfis, D. Thalmann, D. Kao, & L. Avila (Eds.), Advances in Visual Computing (pp. 163–172). Lecture Notes in Computer Science. http://hdl.handle.net/20.500.12708/53486 ( reposiTUm)

Zambanini, S., & Kampel, M. (2009). Robust Automatic Segmentation of Ancient Coins. In 4th International Conference on Computer Vision Theory and Applications (pp. 273–276). http://hdl.handle.net/20.500.12708/52902 ( reposiTUm)

Zambanini, S., Herrmann, M., & Kampel, M. (2009). An Automatic Method to Determine the Diameter of Historical Coins in Images. In Scientific Computing for Cultural Heritage SCCH 2009. Scientific Computing for Cultural Heritage, SCCH2009, Heidelberg, EU. http://hdl.handle.net/20.500.12708/52905 ( reposiTUm)

Zambanini, S., Blauensteiner, P., & Kampel, M. (2009). Automated Multi-Camera Surveillance for the Prevention and Investigation of Bank Robberies in Austria: A Case Study. In Proceedings. 3rd international Conference on Imaging for Crime Detection and Prevention, London, EU. http://hdl.handle.net/20.500.12708/52908 ( reposiTUm)

Herrmann, M., Kampel, M., & Zambanini, S. (2009). Image Based Measurement of Ancient Coins. In Proceedings of the 37th Annual Conference on Computer Applications and Quantitative Methods in Archaeology (CAA’09). 37th Annual Conference on Computer Applications and Quantitative Methods in Archaeology (CAA’09), Williamsburg, Virginia, USA, Non-EU. http://hdl.handle.net/20.500.12708/52907 ( reposiTUm)

Zambanini, S., Schlapke, M., Müller, A., & Kampel, M. (2009). Acquisition of 3D Coin Models and Their Potential in Numismatic Research. In Konferenzband EVA 2009 Berlin. EVA Berlin 2009, Berlin, EU. http://hdl.handle.net/20.500.12708/52906 ( reposiTUm)

Zambanini, S., Schlapke, M., & Kampel, M. (2009). Historical Coins in 3D: Aquisition and Numismatic Applications. In 10th International Symposium on Virtual Reality, Archaeology and Cultural Heritage - VAST-STAR, Short and Project Proceedings (pp. 49–52). http://hdl.handle.net/20.500.12708/52903 ( reposiTUm)

Zambanini, S., & Kampel, M. (2008). Segmentation of Ancient Coins Based on Local Entropy and Gray Value Range. In J. Pers (Ed.), Proceedings of the 13th Computer Vision Winter Workshop (CVWW’08). http://hdl.handle.net/20.500.12708/52355 ( reposiTUm)

Zambanini, S., Kampel, M., & Schlapke, M. (2008). On the Use of Computer Vision for Numismatic Research. In Proceedings of the 9th International Symposium on Virtual Reality, Archaeology and Cultural Heritage (VAST’08). 9th International Symposium on Virtual reality, Archaeology, and Cultural Heritage, Braga, Portugal, EU. http://hdl.handle.net/20.500.12708/52356 ( reposiTUm)

Kampel, M., Vondrovec, K., Zaharieva, M., & Zambanini, S. (2008). Image-Based Classification Of Ancient Coins. In Proceedings of the 14th International Conference on Virtual Systems and Multimedia. VSMM09, Limassol, Cyprus, EU. http://hdl.handle.net/20.500.12708/52590 ( reposiTUm)

Zaharieva, M., Kampel, M., & Zambanini, S. (2007). Image based recognition of ancient coins. In W. Kropatsch, M. Kampel, & A. Hanbury (Eds.), Computer Analysis of Images and Patterns (pp. 547–554). Springer Lecture Notes in Computer Science. http://hdl.handle.net/20.500.12708/51975 ( reposiTUm)

Zaharieva, M., Kampel, M., & Zambanini, S. (2007). Image based recognition of coins -- An Overview of the COINS project. In Performance Evaluation for Computer Vision 31st AAPR/OAGM Workshop 2007 (pp. 57–64). http://hdl.handle.net/20.500.12708/51821 ( reposiTUm)

Zambanini, S., Langs, G., Sablatnig, R., Donath, P., & Maier, H. (2007). Automatic Robust Registration of Cutaneous Hemangiomas for Follow-up Examinations. In Performance Evaluation for Computer Vision 31st AAPR/OAGM Workshop 2007 (pp. 121–128). OCG. http://hdl.handle.net/20.500.12708/51818 ( reposiTUm)

Zambanini, S., Langs, G., Sablatnig, R., Donath, P., & Maier, H. (2006). Automatic Surveying of Cutaneous Hemangiomas. In 18th International Conference on Pattern Recognition (pp. 1022–1025). http://hdl.handle.net/20.500.12708/51497 ( reposiTUm)

Zambanini, S., Langs, G., & Bischof, H. (2005). Segmentation and Surveying of Cutaneous Hemangiomas. In A. Hanbury & H. Bischof (Eds.), Proceedings of Computer Vision Winter Workshop CVWW (pp. 103–112). Eigenverlag. http://hdl.handle.net/20.500.12708/51297 ( reposiTUm)

Kampel, M., & Zambanini, S. (2015). Shape Analysis and Geometric Modelling. In Mathematics and Archaeology (pp. 137–156). CRC Press. http://hdl.handle.net/20.500.12708/28778 ( reposiTUm)

Jarrett, J., Zambanini, S., Huber-Mörk, R., & Felicetti, A. (2012). Coinage, Digitization, and the World-Wide Web: Numismatics and the COINS Project. In B. Nelson & M. Terras (Eds.), Digitizing Medieval and Early Modern Material Culture (pp. 455–485). Iter, Inc., and the Arizona Center for Medieval and Renaissance Studies. http://hdl.handle.net/20.500.12708/27745 ( reposiTUm)

Huber-Mörk, R., Nölle, M., Rubik, M., Hödlmoser, M., Zambanini, S., & Kampel, M. (2012). Automatic Coin Classification and Identification. In Advances in Object Recognition Systems. InTech. https://doi.org/10.5772/35795 ( reposiTUm)

Zambanini, S., & Sablatnig, R. (2017). Adapting to the Problem at Hand: Image Registration and Object Detection for Automatic WW2 Aerial Photograph Processing. 45th Computer Applications and Quantitative Methods in Archaeology Conference (CAA 2017), Atlanta, United States of America (the). http://hdl.handle.net/20.500.12708/86632 ( reposiTUm)

Zambanini, S., Hollaus, F., & Sablatnig, R. (2016). Computer Vision applied to Historical Air Photos: The Registration and Object Detection Challenge. 44th Computer Applications and Quantitative Methods in Archaeology Conference (CAA 2016), Oslo, Norway. http://hdl.handle.net/20.500.12708/86372 ( reposiTUm)

Kavelar, A., Zambanini, S., & Kampel, M. (2014). Concluding ILAC - An Interdisciplinary Approach towards Image-Based Classification of Ancient Coins. 42nd Computer Applications and Quantitative Methods in Archaeology Conference (CAA 2014), Paris, France. http://hdl.handle.net/20.500.12708/85902 ( reposiTUm)

Zambanini, S. (2012). Computergestützte Bestimmung Antiker Münzen. Forschung im Museum, Kunsthistorisches Museum, Wien, Austria. http://hdl.handle.net/20.500.12708/84905 ( reposiTUm)

Kavelar, A., Zambanini, S., & Kampel, M. (2012). Automatically Recognizing the Legends of Ancient Roman Republican Coins. Computer Applications and Quantitative Methods in Archaeology (CAA) 2012, Southampton, Großbritannien, EU. http://hdl.handle.net/20.500.12708/85449 ( reposiTUm)

Zambanini, S., & Kampel, M. (2011). An Automatic Image Based Coin Classification System for Numismatic Databases. CHNT 2011 16th International Conference on Cultural Heritage and New Technologies, Wien, Österreich, Austria. http://hdl.handle.net/20.500.12708/85299 ( reposiTUm)

Baldauf, M., Zambanini, S., Lasinger, K., & Reichl, P. (2011). Towards Markerless Visual Finger Detection for Gestural Interaction with Mobile Devices. Workshop on Smart Mobile Applications, San Francisco, USA, Non-EU. http://hdl.handle.net/20.500.12708/85179 ( reposiTUm)

Zambanini, S., Kampel, M., & Machajdik, J. (2010). Computer Vision for an Independent Lifestyle of the Elderly - An Overview of the MuBisA Project. AALIANCE Conference, Malaga, Spanien, EU. http://hdl.handle.net/20.500.12708/85023 ( reposiTUm)

Zambanini, S. (2014). Insensitive image comparison in the absence of training data [Dissertation, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2014.25346 ( reposiTUm)

Zambanini, S. (2007). Automatic assessment of lesion development in hemangioma follow-up images [Master Thesis, Technische Universität Wien]. reposiTUm. http://hdl.handle.net/20.500.12708/179412 ( reposiTUm)