3 months ago

_VIA Autumn 2018 FINAL proof

_VIA Autumn 2018 FINAL

Editor: Dr Denis Bulgin Advertising Sales & Production: Chris Valde s Autumn 2018 Industr y update from the UK Industrial Vision Association Deep learning for machine vision Image courtesy Framos The use and availability of deep learning techniques for machine vision is generating a huge amount of interest in the industry as a whole. With standing room only for deep learning at this year’s UKIVA Machine Vision Conference, our centre pages are devoted to this popular topic. The evolution of deep learning Deep learning is a subset of machine learning, which in turn is part of the overall umbrella of artificial intelligence (AI). AI was first formulated as far back as 1956. In the 1980s, machine learning emerged in the form of algorithms that can learn patterns in training data sets using some form of statistical analysis, then look for those same patterns in ‘unknown’ data. Deep learning, however, utilises artificial neural networks to imitate the way the human brain works for recognition and decision making. Deep learning really began to make an impact around 2012 thanks to a number of key breakthroughs. These included the development of deep neural networks with many hidden layers, the possibility of massive parallel processing at affordable costs through GPUs, large data storage capabilities and the availability of huge data sets for training. Now deep learning capabilities for machine vision are available through commercial image processing software. Extraordinarily powerful, but not a magic bullet in solving all imaging problems. Recognition 3 Reading 3 Detection 3 What’s good and what’s not - more information on deep learning in the centre pages. Matching 7 Decoding 7 Measuring 7 Deep learning capabilities (Courtesy Matrox Imaging) Matrox Imaging See our advert on page 21 Stemmer Imaging See our advert on page 22 IDS Imaging See our adverts on page 29 Cognex See our advert on page 30

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