Aug 1 – 5, 2022
GMT timezone
*** Thanks to everyone for making this a successful conference - See you in person for RT2024 (April) ***

Automated visual inspection of silicon detectors in CMS experiment

Not scheduled
20m
Poster plus Minioral Deep Learning and Machine Learning Mini Oral - III

Speaker

Mr CHHABRIA, AMIT

Description

In the Compact Muon Solenoid (CMS) experiment at CERN, Geneva, a large number of High-granularity calorimeter (HGCAL) sensor modules are fabricated in advanced laboratories around the world. Each sensor module contains about 700 checkpoints for visual inspection thus making it almost impossible to carry out such inspection manually. As artificial intelligence is more and more widely used in manufacturing, traditional detection technologies are gradually being intelligent. In order to more accurately evaluate the checkpoints, we propose to use deep learning-based object detection techniques to detect manufacturing defects in testing large numbers of modules automatically.

Minioral Yes
IEEE Member No
Are you a student? Yes

Primary authors

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