In the field of image recognition, the scale and diversity of datasets are crucial for model training. This study proposes a novel cross-validation dataset pruning method with data balancing (CVDP-DB) ...
The U.S. healthcare system generates massive volumes of data spanning patients, treatments, and billing but real datasets are often inaccessible due to privacy laws like HIPAA. This project was ...
Abstract: Photovoltaic (PV) modules are crucial components in solar power generation, where their efficiency and safety can be compromised by various defects. Infrared images of PV modules can be used ...
Data is the oil that fuels the AI gold rush; machines need it to understand the world and help us solve its most pressing problems. But the way we use, collect and store data is evolving as quickly as ...
Custom market research has always been notoriously slow and costly to conduct, often requiring many months and significant investments. As a result, marketers have made many strategic decisions ...
StratifAI, the AI precision oncology company behind the Polaris™ platform, today announced its selection for the Memorial Sloan Kettering (MSK) iHub Challenge 2025 Cohort program. This engagement will ...
ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...
The Common Data Set can help prospective students know how much aid they could get to pay for college. Why don’t all schools provide it? By Ron Lieber A similar version of this column was published ...
The comparison of model outputs with ground-measured data from reference stations ensures the accuracy of solar models and reduces uncertainty across all climates. Image: Solargis. When selecting ...
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