Books, book chapters, dissertations
-
(2023): Image classification and retrieval in the context of silk heritage using deep learning. In: Wissenschaftliche Arbeiten der Fachrichtung Geodäsie und Geoinformatik der Leibniz Universität Hannover, ISSN 0174-1454, Nr. 390, Dissertation, Hannover. | File |
Peer reviewed journal papers
-
(2022): Deep descriptor learning with auxiliary classification loss for retrieving images of silk fabrics in the context of preserving European silk heritage. ISPRS International Journal of Geo-Information 11(2), paper 82
DOI: 10.3390/ijgi11020082 -
(2022): Multimodal metadata assignment for cultural heritage artifacts, In: Multimedia Systems, 1-23.
DOI: 10.1007/s00530-022-01025-2 -
(2020): From silk to digital technologies: A gateway to new opportunities for creative industries, traditional crafts and designers. The SILKNOW case, In: Sustainability 12(19), paper 8279. More info
DOI: 10.3390/su12198279
Peer reviewed conference papers
-
(2024): Multi-modal land cover classification of historical aerial images and topographic maps: a comparative study. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-4-2024, pp. 107-115.
DOI: 10.5194/isprs-annals-X-4-2024-107-2024 -
(2024): Enhancing Multi-Sensor Land Cover Classification Through Transformer-Based Utilization of Satellite Image Time Series, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-3-2024, 169–177.
DOI: 10.5194/isprs-annals-X-3-2024-169-2024 -
(2023): Addressing class imbalance for training a multi-task classifier in the context of silk heritage, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1/W1-2023, 175–184.
DOI: 10.5194/isprs-annals-X-1-W1-2023-175-2023 -
(2021): Searching silk fabrics by images leveraging on knowledge graph and domain expert rules. In: SUMAC'21: Proceedings of the 3rd Workshop on Structuring and Understanding of Multimedia heritAge, pp. 41–49.
DOI: https://doi.org/10.1145/3475720.3484445 -
(2020): Assessing the semantic similarity of images of silk fabrics using convolutional neural networks. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-2, pp. 641–648. More info
DOI: 10.5194/isprs-annals-V-2-2020-641-2020 -
(2019): Multi-task deep learning with incomplete training samples for the image-based prediction of variables describing silk fabrics. In: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W6, pp. 47–54.
DOI: 10.5194/isprs-annals-IV-2-W6-47-2019
Non-reviewed conference papers
-
(2022): DEEP LEARNING-BASED TRACKING OF MULTIPLE OBJECTS IN THE CONTEXT OF FARM ANIMAL ETHOLOGY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 509–516
DOI: 10.5194/isprs-archives-XLIII-B2-2022-509-2022 -
(2022): ADDRESSING CLASS IMBALANCE IN MULTI-CLASS IMAGE CLASSIFICATION BY MEANS OF AUXILIARY FEATURE SPACE RESTRICTIONS , Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 777–785
DOI: 10.5194/isprs-archives-XLIII-B2-2022-777-2022 -
(2021): Artificial intelligence meets cultural heritage: image classification for the prediction of semantic properties of silk fabrics. Weaving Europe. Silk Heritage and Digital Technologies, ISBN 978-84-18656-97-2, pp.147-166, Tirant lo Blanch, Valencia (Spain) More info
-
(2019): Deep Learning zur Analyse von Bildern von Seidenstoffen für Anwendungen im Kontext der Bewahrung des kulturellen Erbes. 39. Wissenschaftlich-Technische Jahrestagung der DGPF und Dreiländertagung der OVG, DGPF und SGPF in Wien, Publikationen der DGPF Band 28, 387-399. More info
