Abstract: Multi-label classification is a fundamental task that requires predicting all applicable labels for each sample. Previous methods often rely heavily on training models with large-scale multi ...
Abstract: Multi-label image classification, which involves recognizing multiple objects within a single image, is a fundamental task in computer vision. Recently, Visual-Language Models (VLMs) have ...
BiLSTM, an ICD-11 automatic coding model using MC-BERT and label attention. Experiments on clinical records show 83.86% ...
A Husqvarna researcher developed a fast, interpretable PV hotspot-detection method using IR thermography and Lab* color-space features instead of heavy neural networks, achieving up to 95.2% accuracy ...
Colon cancer classification has a significant guidance value in clinical diagnoses and medical prognoses. The classification of colon cancers with high accuracy is the premise of efficient treatment.
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