The DOL proposed a new rule to simplify independent contractor classification, reverting to a framework similar to the 2021 ...

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 ...

Data classification labels are critical to the effective management and protection of information based on its sensitivity and the potential impact of disclosure. These labels enable the University to ...

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

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 ...

ABSTRACT: The quantification and evaluation of ecosystem services represent key drivers for the sustainable development of human activities, particularly within the framework of natural capital ...

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 ...

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 ...

Colorectal cancer is the third most common cancer worldwide, and accurate pathological diagnosis is crucial for clinical intervention and prognosis assessment. Although deep learning has shown promise ...