Abstract: Multi-label emotion classification (MLEC) for low-resource languages like Arabic faces significant challenges due to class imbalance and label correlations, particularly in accurately ...

Electronic medical records (EMRs) enable healthcare institutions to digitally document patients’ clinical conditions, treatment processes, and diagnostic outcomes, supporting paperless clinical ...

Photoshop CS6 Extended tutorial showing how to customize an existing wine label with your own name and then place it onto an image of a wine bottle. Areas covered include the warp transform tool, ...

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

ClickFix attacks have evolved to feature videos that guide victims through the self-infection process, a timer to pressure targets into taking risky actions, and automatic detection of the operating ...

The multi-part labels market size is estimated to be worth USD 1.87 billion in 2025 and is anticipated to reach a value of USD 3.11 billion by 2035. Sales are projected to rise at a CAGR of 5.2% over ...

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 ...

I tried applying label smoothing to my multi-label classification problem—given that my dataset is noisy and unbalanced, I thought it might help—but I ran into issue #40258 ...

In the published article, there was an error in the Funding statement. The Funding statement was erroneously omitted, and financial support grants should have instead ...

Active learning for multi-label classification addresses the challenge of labelling data in situations where each instance may belong to several overlapping categories. This paradigm aims to enhance ...