Given that research on deep active learning techniques in the context of foundation models is limited ... human annotation, and model training in a cycle, deep active learning approaches relate to ...

The study aims to employ deep learning models to identify defects in a 3D-printed ... Additionally, the study has revealed that the number of times the test set is applied to the trained model ...

Three recent studies by data-engineering specialist Swaminathan Sethuraman map out an efficiency agenda for the next ...

Appropriate Model for Evaluating the States, Stability, and Changes of Deep Approaches to Learning Before identifying the appropriate model for evaluating the states, stability, and changes of deep ...

In response, we present SAMMS, an advanced multi-omics multimodal deep learning framework tailored for survival prediction. SAMMS leverages the robust image segmentation model, "Segment Anything" to ...

Some researchers remain skeptical that the theory fully accounts for the success of deep learning, but Kyle Cranmer, a particle physicist at New York University who uses machine learning to analyze ...