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AIA’s director of education strategies, who says that the aim is to ensure the curriculum meets industry needs. ‘We looked at the courses and saw that attention to machine vision was peppered throughout,’ Huschka said. ‘But we decided we really needed a course focused entirely on machine learning.’ AIA is also reviewing
its content for embedded vision and autonomous navigation, to see whether or not these topics need more independent coverage. Technology is not all that is driving such
Partnering with
programme, so we can come out on the other side with a 21st century learning experience. We’re sensitive to the fact that people learn in different ways, and there are new tools available now.’ For example, AIA is
academic and industry certification programmes... will continue to be an important strategy for vision companies
exploring the idea of adding online training, expanding the pool of instructors, and looking for ways to make the courses more experiential. Te goal is to make the coursework more attractive to more students,
while delivering an education that meets the needs of industry today.
curriculum reviews. Te nature and tools of learning are as well. Another key goal in CVP’s review processes is to examine how to best deliver the content. ‘We’re focused on the experience,’ Shikany
said. ‘So, we’re taking the opportunity during this process to interview people and companies who have used the CVP
Attracting more candidates Adapting training programmes to a constantly evolving industry is a perpetual process. But before you can train talent, you must first attract it. Te challenge for the machine vision industry is finding ways to make machine vision engaging. According to James Gardiner, business development manager for Metaphase
Technologies, the robotics industry has an edge over machine vision in this regard. ‘With robotics, the students can physically touch the solution and see it working. For machine vision, unfortunately, we’re more of a black box,’ he said. Fortunately, vision is an increasingly
pervasive technology, in industries as diverse as automotive, consumer electronics, medicine and manufacturing. Partnering with academic and industry certification programmes serving these sectors will continue to be an important strategy for vision companies. Tere is no quick or enduring answer
to the machine vision industry’s need for qualified talent, unless constant adaptation is the answer. As academia’s growing attention to imaging and its specialities demonstrates, there is awareness of the demand, and we can expect both demand and awareness to grow as machine vision solutions become a more common part of consumer experiences. But smart companies won’t wait to capitalise on training as an important tool for recruitment, retention and competitiveness. O
Yearbook 2019/2020 • Imaging and Machine Vision Europe 25
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