The AI tool improves upon a process called medical image segmentation, where every pixel in an image is labeled based on what it represents — cancerous or normal tissue, for example. This process is ...

Joint research led by Sosuke Ito of the University of Tokyo has shown that nonequilibrium thermodynamics, a branch of physics ...

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine ...

Our method involves modeling image features as a nine-dimensional feature vector, followed by a dimensionality reduction process to identify the most influential features and dominant areas within the ...

Technological advancements have profoundly transformed the sports domain, ushering it into the digital era. Services ...

The disease is known for its strong association with climatic variables, especially excessive rainfall, high humidity, and ...

They applied machine learning techniques for feature extraction and image classification of TCI, concluding that multilayer perceptron models achieved an accuracy of 90.1% (16).

The newly developed intervention, called MODERN (Machine-learning-assisted Optimizing Dietary intERvention against demeNtia risk), was introduced in a paper in Nature Human Behavior.

The models currently used for polarimetric synthetic aperture radar (PolSAR) image classification tasks have problems, such as complex network structures, poor distinction of detailed features, and ...

The methodology involved gathering PRS-11 questionnaire data, performing street map crawling and prediction, conducting large-scale analysis of 114 student image evaluations using a CNN-BiLSTM-based ...