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 ...

Demographic bias gaps are closing in face recognition, but how training images are sourced is becoming the field’s biggest privacy fight.

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 ...

A deep-learning analysis of three-dimensional optical coherence tomography scans shows promising accuracy in distinguishing ...

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.

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.

Researchers propose LEAF, a frontend for developing AI classification algorithms Kyle Wiggers @Kyle_L_Wiggers January 25, 2021 1:00 PM Amazon Echo Dot Clock ...

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

In addition, all solutions are based on clever designs of DNNs and data augmentations, but provide little insight beyond the “black box”–type classification algorithms.