When life sciences startups think about patent strategy, the natural instinct is to focus on the core science — the novel compound, the ...

Every AI model depends on labeled data. Data annotation is the process of tagging images, text, audio, or video so that ...

A prescription label isn't always as clear as it looks, and when instructions get misread or don't fully stick, it can lead ...

Our approach models label noise in semantic segmentation with a probabilistic framework that incorporates spatial correlations. By introducing a continuous latent ...

The label correction was estimated to bring about a 12.5% enhancement in the estimated sensitivity of the DL algorithm (P<.001). Conclusions: Label errors based on human image grading, although in a ...

Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

Abstract: A typical speaker recognition system often involves two modules: a feature extractor front-end and a speaker identification back-end. Despite the superior performance that deep neural ...

Abstract: Partial-label learning (PLL) aims to solve the problem where each training instance is associated with a set of candidate labels, one of which is the correct label. Most PLL algorithms try ...