Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2022; 31st International C Elias Pimenidis,Plamen Angelov,Mehmet Aydin Conference p

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Exploring Deep Learning Architectures for Localised Hourly Air Quality Prediction,n context, we propose that as a decision support tool it is more valuable to provide hourly forecasts at local scales with the following considerations: (1) the system should be designed for rapid and simple human-tuning of different trade-offs; (2) the chosen model and hyper-parameters should maxim

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,F-Transformer: Point Cloud Fusion Transformer for Cooperative 3D Object Detection,ded, or small objects). Building on a two-step communication scheme to transmit the pillar features between views, it is possible to observe the same object from different viewpoints. We then design a feature fusion scheme based on Transformer to fuse the pillar features by discretizing the point cl

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How to Face Unseen Defects? UDGAN for Improving Unseen Defects Recognition,ad to large economic losses. Existing methods focus on the recognition of seen defects, but are powerless against unseen defects. The recognition of unseen defects is a challenging task and has not been widely explored. To our knowledge, we are the first to raise the issue of unseen defect recogniti

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,Lymphoma Ultrasound Image Segmentation with Self-Attention Mechanism and Stable Learning,f lymphoma ultrasound images: (i) the fuzziness of structural boundaries in the image domain and (ii) the generalization of images scanned by different ultrasonic instruments. To solve these two problems, we propose an segmentation framework based on self-attention mechanism and stable learning, in

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Elektrochemisches Abtragen (ECM),l image. Then, in order to solve the problem of curve deviation and curve defect, two components, curve correction and curve filling, which adopt deep regression and Generative adversarial networks, are devised for spectrum curve refining operation. These two outputs are fused for final segmentation

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