Abstract: The number of categories of instances in the real world is normally huge, and each instance may contain multiple labels. To distinguish these massive labels utilizing machine learning, ...

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 ...

In an era of rapidly growing multimedia data, the need for robust and efficient classification systems has become critical, specifically the identification of class names and poses or styles. This ...

The agency issued designs for front-of-package lists that food companies would be required to include. By Andrew Jacobs The Food and Drug Administration on Tuesday proposed requiring new nutrition ...

Abstract: Multi-view multi-label classification is a crucial machine learning paradigm aimed at building robust multi-label predictors by integrating heterogeneous features from various sources while ...

1 School of Media & Communication Shanghai Jiao Tong University, Shanghai, China 2 Department of Critical Care Medicine, Sir Run Run Shaw Hospital, Hangzhou, Zhejiang, China Objective: This study ...

To help you better understand the type of data with which you interact, UAB IT will enable data classification labels for files in the Microsoft 365 environment on Dec. 6. Labels correspond to UAB’s ...