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20172026
most citedAutomatic Classification of Defective Photovoltaic Module Cells in Electroluminescence Images

564 citations · 1.1k across the 64 of their papers we have counts for

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Showing 2024Show all

8 papers · 1 filter

cs.CV2024

Gesture Classification in Artworks Using Contextual Image Features

Azhar Hussian, Mathias Zinnen, Thi My Hang Tran +2

Recognizing gestures in artworks can add a valuable dimension to art understanding and help to acknowledge the role of the sense of smell in cultural heritage. We propose a method…

cs.CV2024

Nuremberg Letterbooks: A Multi-Transcriptional Dataset of Early 15th Century Manuscripts for Document Analysis

Martin Mayr, Julian Krenz, Katharina Neumeier +8

Most datasets in the field of document analysis utilize highly standardized labels, which, while simplifying specific tasks, often produce outputs that are not directly applicable…

cs.CV2024★ 8 cited

Zero-Shot Paragraph-level Handwriting Imitation with Latent Diffusion Models

Martin Mayr, Marcel Dreier, Florian Kordon +5

The imitation of cursive handwriting is mainly limited to generating handwritten words or lines. Multiple synthetic outputs must be stitched together to create paragraphs or whole…

cs.CV2024

Novel Artistic Scene-Centric Datasets for Effective Transfer Learning in Fragrant Spaces

Shumei Liu, Haiting Huang, Mathias Zinnen +2

Olfaction, often overlooked in cultural heritage studies, holds profound significance in shaping human experiences and identities. Examining historical depictions of olfactory scen…

cs.CV2024★ 1 cited

Smell and Emotion: Recognising emotions in smell-related artworks

Vishal Patoliya, Mathias Zinnen, Andreas Maier +1

Emotions and smell are underrepresented in digital art history. In this exploratory work, we show that recognising emotions from smell-related artworks is technically feasible but…

cs.CV2024★ 66 cited

Offline Writer Identification Using Convolutional Neural Network Activation Features

Vincent Christlein, David Bernecker, Andreas Maier +1

Convolutional neural networks (CNNs) have recently become the state-of-the-art tool for large-scale image classification. In this work we propose the use of activation features fro…