The first job for many artificial intelligence (AI) algorithms is to examine the data and find the best classification. An autonomous car, for example, may take an image of a street sign; the ...

Multi-label: The researchers trained the algorithm for multi-label skin classification, i.e. it can differentiate between five different categories of skin lesions.

Which kind of algorithm works best (supervised, unsupervised, classification, regression, etc.) depends on the kind of problem you’re solving, the computing resources available, and the nature ...

The image classification algorithm takes an image as input and outputs a probability for each provided class label. Training datasets must consist of images in .jpg, .jpeg, or .png format.

where n is the grand total of ED visits, c is the number of columns in a classification table, and r is the number of visit classes. The P value for the significance of V is the same as for ...

Here's one way to reduce them Image classification algorithms are notoriously error-prone, but a novel method for spotting errors within incomprehensible AI code could help solve the problem.