AI News, Approaches to Multimodal Digital Environments: from theories to ... artificial intelligence
Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology
In the past decade, advances in precision oncology have resulted in an increased demand for predictive assays that enable the selection and stratification of patients for treatment.
The possibility of digitizing whole-slide images of tissue has led to the advent of artificial intelligence (AI) and machine learning tools in digital pathology, which enable mining of subvisual morphometric phenotypes and might, ultimately, improve patient management.
Facial movements play a crucial role for human beings to communicate and express emotions since they not only transmit communication contents but also contribute to ongoing processes of emotion-relevant information.
To diminish the influences of such diversity, we propose to characterize the dynamics of short-term movements via the differences between points on the tangent spaces to the manifolds, rather than the points themselves.
We then significantly relax the trajectory-smooth assumption of the conventional manifold based trajectory modeling method and model longer-term dynamics using statistical observation model within the sequential inference approaches.
proposed motion elucidation and description approach is validated by a series of experiments on publicly available datasets in the example tasks of micro-expression recognition and visual speech recognition.