Prathmesh Madhu

Prathmesh Madhu, M. Sc.


Department of Computer Science
Chair of Computer Science 5 (Pattern Recognition)

Room: Room 09.156
Martensstr. 3
91058 Erlangen

Academic CV

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  • ICONOGRAPHICS: Computational Understanding of Iconography and Narration in Visual Cultural Heritage

    (FAU Funds)

    Term: April 1, 2019 - March 31, 2021

    The interdisciplinary research project Iconographics is dedicated to innovative possibilities of digital image recognition for the arts and humanities. While computer vision is already often able to identify individual objects or specific artistic styles in images, the project is confronted with the open problem of also opening up the more complex image structures and contexts digitally. On the basis of a close interdisciplinary collaboration between Classical Archaeology, Christian Archaeology, Art History and the Computer Sciences, as well as joint theoretical and methodological reflection, a large number of multi-layered visual works will be analyzed, compared and contextualized. The aim is to make the complex compositional, narrative and semantic structures of these images tangible for computer vision.

    Iconography and Narratology are identified as a challenging research questions for all subjects of the project. The iconography will be interpreted in its plot, temporality, and narrative logic. Due to its complex cultural structure; we selected four important scenes:

    1. The Annunciation of the Lord
    2. The Adoration of the Magi
    3. The Baptism of Christ
    4. Noli me tangere (Do not touch me)


  • Automatic Intraoperative Tracking for Workflow and Dose Monitoring in X-Ray-based Minimally Invasive Surgeries

    (Third Party Funds Single)

    Term: June 1, 2018 - May 31, 2021
    Funding source: Bundesministerium für Bildung und Forschung (BMBF)

    The goal of this project is the investigation of multimodal methods for the evaluation of interventional workflows in the operation room. This topic will be researched in an international project context with partners in Germany and in Brazil (UNISINOS in Porto Alegre). Methods will be developed to analyze the processes in an OR based on signals from body-worn sensors, cameras and other modalities like X-ray images recorded during the surgeries. For data analysis, techniques from the field of computer vision, machine learning and pattern recognition will be applied. The system will be integrated in a way that body-worn sensors developed by Portabiles as well as angiography systems produced by Siemens Healthcare can be included alongside.



Unpublished Publications


Conference Contributions


Conference Contributions



Journal Articles

Conference Contributions


Conference Contributions


Journal Articles

Conference Contributions


Conference Contributions


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Title Type Start/end date Student
Implementation of an automated optical inspection (AOI) system for the automatic visual inspection of an enclosure assy DC distribution MA thesis November 14, 2022 - April 13, 2023 Mark Antoine Turban Ndjeuha
Improving Instance Localization for Object Detection Pretraining MA thesis August 1, 2022 - February 1, 2023 Jonas Miksch
Exploring Style-transfer techniques on Greek vase paintings for enhancing pose-estimation BA thesis November 18, 2021 - April 12, 2022 Wolfgang Meier
Similarity and duplicate search in artwork images MA thesis October 8, 2021 - April 7, 2022 Yinan Shao
Enhanced Generative Learning Methods for Real-World Super-Resolution Problems in Smartphone Images BA thesis June 21, 2021 - November 21, 2021 Alexander Schmidt
Content-based Image Retrieval based on compositional elements for art historical images BA thesis November 27, 2020 - April 27, 2021 Tilman Marquart
Pose Based Image Retrieval in Greek Vase Paintings MA thesis June 1, 2020 - November 30, 2020 Angel Villar-Corrales