The continued burning of fossil fuels is locking heat in Earth’s atmosphere, oceans and land — instead of allowing it to reflect back into space, a new report finds. By Eric Niiler The Earth is out of ...

Abstract: In machine learning (ML), class imbalance is a serious problem when datasets with a dominating majority class make it difficult to accurately classify minority samples. Traditional methods ...

A Pytorch U-Net implementation for Retinal Vessel Segmentation on DRIVE dataset. Features CLAHE preprocessing and Hybrid Loss to handle class imbalance.

The demand and supply of new skills—especially in IT and AI—are reshaping labor markets, impacting wages and hiring. About one in ten job vacancies in advanced economies demands at least one new skill ...

Since the start of his second term, U.S. President Donald Trump has been dismantling the traditional channels of American soft power. The U.S. Agency for International Development (USAID) is no longer ...

Binary cross-entropy (BCE) is the default loss function for binary classification—but it breaks down badly on imbalanced datasets. The reason is subtle but important: BCE weighs mistakes from both ...

Do you know what your hormone levels are? Should you? Your body is home to more than 50 hormones — chemical messengers that compose the endocrine system — and hormonal changes may reflect any number ...

Abstract: In many real-world datasets, the class distribution is often highly imbalanced, and minority class samples are located within the majority regions, leading to significant overlap. These ...

If you’re a woman in your forties or fifties, you’re probably no stranger to the flood of advice and solutions flying at you from every corner of the internet about balancing your hormones. But what ...