References [1] Deep learning, geometric characterization and hydrodynamic modeling for assessing sewer defect impacts on urban flooding: A case study in Guangzhou, China. Journal of Environmental ...

This new technical paper titled “End-to-end deep learning framework for printed circuit board manufacturing defect classification” is from researchers at École de technologie supérieure (ÉTS) in ...

Researchers have tested eight stand-alone deep learning methods for PV cell fault detection and have found that their accuracy was as high as 73%. All methods were trained and tested on the ELPV ...

This paper will focus on how to utilize Onto Innovation’s TrueADC software product to build ADC classifiers using a multi-engine (ME) solution. The software supports CNN, DNN and KNN algorithms. The ...

More information: Zhongshu Ren et al, Sub-millisecond keyhole pore detection in laser powder bed fusion using sound and light sensors and machine learning, Materials Futures (2024). DOI: 10.1088 ...

Oct. 14, 2022 — A new deep-learning framework is speeding up the process of inspecting additively manufactured metal parts using X-ray computed tomography, or CT, while increasing the accuracy ...

However, defects that are greater than 0.12- to 0.16-inch deep can be seen by subsequent reverberations of the signal in the EMAT approach. These reverberations are caused by the sound bouncing back ...

Advances in deep learning have transformed the field of infrastructure maintenance, particularly in the automated detection and characterisation of defects in sewer pipelines. Leveraging large ...