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Machine vision-based detections of transparent chemical vessels toward the safe automation of material synthesis

Chemistry

Machine vision-based detections of transparent chemical vessels toward the safe automation of material synthesis

L. C. O. Tiong, H. J. Yoo, et al.

Discover how DenseSSD, a cutting-edge deep learning object detector developed by Leslie Ching Ow Tiong and colleagues, enhances safety in robotic chemistry automation by accurately locating transparent chemical vessels with outstanding precision.

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Playback language: English
Abstract
Robot-based automation in chemistry accelerates material development but lacks safety in unsupervised environments. This paper introduces DenseSSD, a deep learning-based object detector, to improve safety by precisely locating transparent chemical vessels. DenseSSD achieves over 95% mean average precision (mAP), significantly outperforming existing detectors. Its robustness across varying conditions (solution colors, camera angles, backgrounds) makes it suitable for diverse lab settings, enhancing safety in automated material synthesis.
Publisher
npj | computational materials
Published On
Feb 22, 2024
Authors
Leslie Ching Ow Tiong, Hyuk Jun Yoo, Nayeon Kim, Chansoo Kim, Kwan-Young Lee, Sang Soo Han, Donghun Kim
Tags
robot-based automation
object detection
safety
deep learning
chemical vessels
material synthesis

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