Characterization of nano-coated micro- and nanostructures by pushing

Liimatainen, Ville; Venäläinen, Janne; Koverola, Mikko; Zhou, Quan; Lyytinen, Jussi; Koskinen, Jari; Rontu, Ville; Berdova, Maria; Franssila, Sami

doi:10.1109/3m-nano.2014.7057329

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Cited by 2 publications

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“…The videos include occurrences of both of the events. The videos were recorded during micromanipulation of a dummy SU-8 chip with dimensions of 250×250×30 μm 3 . The videos were split to separate training and validation sets containing 23 videos (3056 frames) and 21 videos (2545 frames), respectively.…”

Section: B Datamentioning

confidence: 99%

Vision based event classification in robotic micromanipulation

Cenev

Venäläinen

Zhou

2017

2017 International Conference on Manipulation, Automation and Robotics at Small Scales (MARSS)

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Abstract-Autonomous positioning of small objects to create heterogeneous structures has great potential to advance the current micromanipulation procedures. To achieve autonomous micromanipulation, it is required to recognize the manipulation events. In this work, different classification algorithms including five common supervised learning methods are assessed for identifying states of manipulation. The classifiers are trained with data that consists of 3056 video frames and validated on 2545 videos frames. The best machine learning classifiers classified the events with 92.9 % accuracy, higher than the result of logic-based classification (88.9 %).

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Section: B Datamentioning

confidence: 99%