Titlebook: Artificial Intelligence XL; 43rd SGAI Internatio Max Bramer,Frederic Stahl Conference proceedings 2023 The Editor(s) (if applicable) and Th

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Palgrave Studies in Educational Mediahe reliance on manual note-taking is highly inefficient and leads to transcription errors when digitising notes. Speech-to-text applications designed using Automatic Speech Recognition?(ASR) can potentially overcome these errors using post-ASR error correction. Pre-trained language models are increa

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Anja Ballis,Tobias Heinz,Mira Schienagel the shortage of qualified radiologists, there is an increasing burden on healthcare practitioners, which underscores the need to develop reliable automated methods. Despite the development of novel computational techniques, interpreting medical images remains challenging due to noise and varying ac

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https://doi.org/10.1057/9780230509528utilizes pre-trained computer vision models to extract high-level image features, has demonstrated remarkable efficacy in identifying images with similar compositions. However, there is a lack of methods for evaluating the embeddings generated by these models, as conventional loss and performance me

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https://doi.org/10.1057/9780230509528learning techniques, often used for image classification, to benefit dense downstream prediction tasks such as semantic segmentation. The scheme performs supervised patch-level contrastive learning, selecting the patches based on the ground truth mask, subsequently used for hard-negative and hard-po

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Christel G?rtner,Heidemarie Winkelphical region. SAR offers advantages over optical sensors for disaster-related change detection in remote sensing due to its all-weather capability and ability to penetrate clouds and darkness. The performance of change detection methods is affected by several challenges. Deep learning methods, such