Machine learning and deep learning ... for specialized problems, such as image classification and speech recognition, that aren’t well-suited to simpler algorithms. Note that “deep” means ...

A new “periodic table for machine learning,” is reshaping how researchers explore AI, unlocking fresh pathways for discovery. The framework, Information-Contrastive Learning (I-Con), connects diverse ...

Machine learning algorithms can analyze complex images and signals generated by NDT methods like X-Ray radiography and ultrasonic testing to detect defects with higher accuracy and sensitivity than ...

Artificial intelligence has the potential to improve the analysis of medical image data. For example, algorithms based ... autoPET combined imaging and machine learning. The task was to ...

First, we had simple machine learning and AI ... But AI in software testing isn't just about running test cases. Keysight Eggplant Test has also led the way in image-based testing, optical character ...

(Courtesy: Laura Gambini/TCD) A new machine-learning technique has significantly reduced noise in images taken by scanning transmission electron microscopy (STEM). Developed by researchers in Ireland, ...

An automated machine learning program ... scans taken during routine clinical testing. When applying the algorithm to vertebral fracture assessment (VFA) images taken in older women during routine ...

However, machine learning can be used to automate this process by training algorithms to identify defects from images or other data sources. This can help reduce the cost of quality control while ...

Through vast data input, AI learns via machine learning protocols, refining accuracy over time through iterative testing and feedback ... and the machine learning algorithm that helped it learn.

Machine learning algorithms enhance retinopathy of prematurity screening using smartphone images, expanding access in low-resource settings and easing pediatric ophthalmologist workloads.

An automated machine ... clinical testing. The algorithm shortens the timeframe to screen for AAC significantly, taking less than a minute to predict AAC scores for thousands of images, compared ...