Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2023; 32nd International C Lazaros Iliadis,Antonios Papaleonidas,Chrisina Jay Confe

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,Clinical Pixel Feature Recalibration Module for Ophthalmic Image Classification,l ability of CNNs. Our CPF is easily inserted into existing CNNs with negligible overhead. We conduct comprehensive experiments on two publicly available ophthalmic image datasets and CIFAR datasets, and the results show the superiority and generation ability of CPF over advanced attention methods.

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IESBU-Net: A Lightweight Skin Lesion Segmentation UNet with Inner-Module Extension and Skip-Connecthe process of feature fusion between encoder and decoder, which is used to smooth the semantic gap between encoder and decoder caused by skip-connection. We evaluated the proposed model on the ISIC 2017 and ISIC 2018 datasets. The experimental results show that the model achieves a good balance betw

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,Tooth Segmentation from Cone-Beam CT Images Through Boundary Refinement,d to conduct two different works in parallel. One is to directly predict the individual tooth segmentation while the other is to generate an offset map for the refinement. Besides, in order to improve the accuracy of tooth boundary segmentation, a boundary-aware loss is also applied in our method. C