Web: http://arxiv.org/abs/2206.07272

June 16, 2022, 1:13 a.m. | Leslie Ching Ow Tiong, Hyuk Jun Yoo, Na Yeon Kim, Kwan-Young Lee, Sang Soo Han, Donghun Kim

cs.CV updates on arXiv.org arxiv.org

Although robot-based automation in chemistry laboratories can accelerate the
material development process, surveillance-free environments may lead to
dangerous accidents primarily due to machine control errors. Object detection
techniques can play vital roles in addressing these safety issues; however,
state-of-the-art detectors, including single-shot detector (SSD) models, suffer
from insufficient accuracy in environments involving complex and noisy scenes.
With the aim of improving safety in a surveillance-free laboratory, we report a
novel deep learning (DL)-based object detector, namely, DenseSSD. For the
foremost …

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