Public datasets of images used to develop dermatology algorithms often don’t label the skin tone or ethnicity of the images. When the images are labeled, most are of light skin.

Researchers at Institut de Robòtica i Informàtica Industrial (CSIC-UPC) and Universitat Politècnica de Catalunya compiled a new dataset that could be used to train robotics algorithms to ...

Self-learning algorithms for different imaging datasets. ScienceDaily. Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2020 / 12 / 201207112253.htm.

Planet paired satellite imagery with machine learning to show the locations of buildings in Cape Coral, Florida, in February 2020. Credit: Planet SAN FRANCISCO – After four years and six ...

Furthermore, in the development of algorithms, we need to ensure that datasets are unbiased. IBM’s AI Fairness 360 is an open source toolkit that helps developers test for bias in their datasets.

This dataset will be used to power a competition hosted by Open Problems in Single-Cell Analysis. Cells are among the most complex and dynamic systems and are regulated by the interplay of DNA ...

"NnU-Net can be used immediately, can be trained using imaging datasets, and can perform special tasks—without requiring any special expertise in computer science or any particularly significant ...

Researchers create global 3D dataset of seawater pH using stepwise FFNN algorithm. Story ... which enhanced the dataset's accuracy. In addition, the use of cross-boundary optimal interpolation ...

To do so, we used a large dataset of facial forgeries that lets researchers like us train our deep-learning approaches. We built our work around the state-of-the-art Xception detection algorithm, ...

We built our work around the state-of-the-art Xception detection algorithm, which is a widely used foundation for deepfake detection systems and can detect deepfakes with an accuracy of 91.5%.