IEEE

Disentangling Consistent and Specific Information for Double Incomplete Multi-View Multi-Label Classification

Abstract: As a prominent research topic, multi-view multi-label classification (MvMlC) aims to assign multiple labels to samples by integrating information from various perspectives. However, in ...
IEEE

Learning Compact Semantic Information and Reliable Pseudo-labels for Incomplete Multi-View Multi-Label Classification

Abstract: Multi-view data encompasses various data types, including multi-feature, multi-sequence, and multi-modal data. Multi-view multi-label classification aims to leverage the rich semantic ...
GitHub

Progressive Uncertainty-Aware Pretraining for Medical X-ray Classification

A novel deep learning framework that combines ImageNet pretraining with uncertainty-aware curriculum learning for robust multi-label chest X-ray classification. The key innovation is an adaptive ...
Frontiers

Evolutionary algorithm-optimized feature fusion for accurate classification of shredded tobacco using multi-sensor data

Individual sensor systems have limitations in the complex task of classifying shredded tobacco. This study aims to overcome these limitations by developing a novel evolutionary algorithm-based feature ...
Microsoft

Multi-Label Classification for Colon Cancer Using Histopathological Images

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.
C&EN

DART Predictor: A Multi-Label Attention Model for High-Throughput Screening of Chemicals with Developmental and Reproductive Toxicity (DART)

State Key Laboratory of Soil Pollution Control and Safety, and Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

The acquisition sites include: CALTECH, California Institute of Technology; CMU, Carnegie Mellon University; KKI, Kennedy Krieger Institute; LEUVEN, University of Leuven; MAX, Ludwig Maximilians ...
GitHub

Single-label multi-classification or multi-label multi-classification?

I have read the paper and it seemed to be a single-label multi-classification problem. But the code use BCE and sigmoid instead of crossEntropy and softmax. So does it mean that the patient may have ...