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Titlebook: Intelligent Systems; 12th Brazilian Confe Murilo C. Naldi,Reinaldo A. C. Bianchi Conference proceedings 2023 The Editor(s) (if applicable)

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51#
發(fā)表于 2025-3-30 10:28:37 | 只看該作者
Dog Face Recognition Using Deep Features Embeddingsbout . of households own at least one pet. Lost and missing dogs are a severe source of suffering and problems for their families. So, this paper addresses the problem of facial dog identification. This technology can benefit many applications, such as handling the missing pet problem, granting pets
52#
發(fā)表于 2025-3-30 14:34:30 | 只看該作者
53#
發(fā)表于 2025-3-30 20:24:18 | 只看該作者
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發(fā)表于 2025-3-30 20:56:32 | 只看該作者
Multi-label Classification of?Pathologies in?Chest Radiograph Images Using DenseNetnce of a DenseNet in a multi-label classification task on radiography images, using focal loss as the loss function to address the class imbalance problem. For the experiments, 14 different types of findings were considered. Satisfactory results were obtained using the area under the ROC curve (AUC-
55#
發(fā)表于 2025-3-31 01:00:55 | 只看該作者
Does Pre-training on?Brain-Related Tasks Results in?Better Deep-Learning-Based Brain Age Biomarkers?ase biomarker. Deep learning models have been established as reliable and efficient brain age estimators, being trained to predict the chronological age of healthy subjects. In this paper, we investigate the impact of a pre-training step on deep learning models for brain age prediction. More precise
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