Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...
Abstract: Recently, Transformer-based few-shot classification methods are widely exploited. However, they only leverage feature information at a single scale, resulting in weak feature representations ...
WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, launched a hybrid quantum neural network structure (H-QNN) ...
Abstract: Semi-supervised multi-view learning is a remarkable but challenging task. Existing semi-supervised multi-view classification (SMVC) approaches mainly focus on performance improvement while ...
Diabetic retinopathy is a serious concern for people dealing with diabetes. Detecting diabetic retinopathy poses significant challenges, requiring skilled professionals, extensive manual image ...
I'm working in a hierarchical multi class problem, and if I flat the labels (flat approach) I have about 1193 classes, which perhaps can already be consider a extreme multi classification problem.
Dr. James McCaffrey of Microsoft Research provides a full-code, step-by-step machine learning tutorial on how to use the LightGBM system to perform multi-class classification using Python and the ...
Alex Alcock is a passionate writer from England, fusing a love of storytelling and gaming to create informative content. He's been involved in game media for less than a year, but has prior experience ...
Aim: To design an automated glaucoma detection system for early detection of glaucoma using fundus images. Background: Glaucoma is a serious eye problem that can cause vision loss and even permanent ...
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