Several image processing tasks, such as image classification and object detection, have
been significantly improved using Convolutional Neural Networks (CNN). Like ResNet and …

Digital health data are multimodal and high-dimensional. A patient's health state can be
characterized by a multitude of signals including medical imaging, clinical variables …

Label smoothing is commonly used in training deep learning models, wherein one-hot
training labels are mixed with uniform label vectors. Empirically, smoothing has been shown …

Objective: Breast cancer is the most common female cancer in the world, and it poses a
huge threat to women's health. There is currently promising research concerning its early …

In self-supervised learning for speaker recognition, pseudo labels are useful as the
supervision signals. It is a known fact that a speaker recognition model doesn't always …

COVID-19 is a disease caused by the SARS-CoV-2 virus. The COVID-19 virus spreads
when a person comes into contact with an affected individual. This is mainly through drops …

This perspective article explores the challenges and potential of using speech as a
biomarker in clinical settings, particularly when constrained by the small clinical datasets …

Regularization of (deep) learning models can be realized at the model, loss, or data level.
As a technique somewhere in-between loss and data, label smoothing turns deterministic …

Digital well-being records are multimodal and high-dimensional (HD). Better
theradiagnostics stem from new computationally thorough and edgy technologies, ie …

We consider a critical issue of false negatives in Vision-Language Pre-training (VLP) a
challenge that arises from the inherent many-to-many correspondence of image-text pairs in …