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One small example: Glass beakers and test tubes are extremely challenging for machine vision systems.
Assesses how knowledge of human perception may be used to guide machine vision systems.
Machine learning approach to machine vision helps in automating the design process of machine vision systems.
Machine vision systems are being increasingly used for sophisticated applications such as classification and process control.
Moreover, biological visual systems are typically far more efficient than current human-made machine vision systems.
The performance of this detector is sufficient to meet the specifications required by machine vision systems.
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Lemelson holds patents on machine-vision systems, an industrial robot, a fax machine, a copy machine, a tape-recorder drive, and a camcorder.
A project run by the Defense Advanced Research Projects Agency DARPAA) suggests that combining the abilities of human sentries with those of machine-vision systems could be a better way to identify danger.
Beyond that, it may be possible to design machine-vision systems that aren't fooled in the same way humans and so could augment human decision making in critical situations such as driving.
The very existence of adversarial images has cast into doubt whether recently developed machine-vision systems bear any real resemblance to humans in terms of how they classify images, and also whether such models can be attacked surreptitiously.
First, and more practically, the existence of adversarial images could invite malicious attacks against machine-vision systems in applied settings (e.g., changing how an autonomous vehicle reads a street sign19).
More suggestions(13)
machine vision methodologies
machine exposure systems
machine vision algorithms
machine repair systems
machine vision topics
machine translation systems
machine intelligence systems
machine guidance systems
machine vision filters
machine vision applications
machine vision techniques
robot vision systems
machine vision sensors
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