Prof. Dr. - Ing. Morris Riedel

Prof. Dr. - Ing. Morris Riedel

Publications

Automatic Object Detection using DBSCAN for Counting Intoxicated Flies in the FLORIDA Assay

Christian Bodenstein, Markus Goetz, Annika Jansen, Henrike Scholz, Morris Riedel
In conference proceedings of the 15th IEEE International Conference on Machine Learning and Applications, IEEE ICMLA’16, Anaheim, USA, 18 Dec 2016 – 20 Dec 2016, ISBN 978-1-5090-6167-9, pp. 746 – 751, 2017
[ EVENT ] [ DOI ] [ JUSER ] [ RESEARCHGATE ]


Object Detection

Abstract:
In this paper, we propose an instrumentation and computer vision pipeline that allows automatic object detection on images taken from multiple experimental set ups. We demonstrate the approach by autonomously counting intoxicated flies in the FLORIDA assay. The assay measures the effect of ethanol exposure onto the ability of a vinegar fly Drosophila melanogaster to right itself. The analysis consists of a three-step approach.

First, obtaining an image of a large set of individual experiments, second, identify areas containing a single experiment, and third, discover the searched objects within the experiment. For the analysis we facilitate well-known computer vision and machine learning algorithms—namely color segmentation, threshold imaging and DBSCAN. The automation of the experiment enables an unprecedented reproducibility and consistency, while significantly decreasing the manual labor.

Social Media

ResearchGate:Paper reached 200 Reads: Automatic Object Detection using #DBSCAN for Counting Intoxicated Flies #HPC #clustering #DataScience @DEEPprojects @fzj_jsc @fz_juelich @Haskoli_Islands @helmholtz_ai @EuroCC_project @uni_iceland @uisens
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More Info: https://t.co/eTn79tEdwU pic.twitter.com/T9sLTnN2zh

— Morris Riedel (@MorrisRiedel) December 1, 2020

ResearchGate: Paper reached 200 Reads: Automatic Object Detection using #DBSCAN for Counting Intoxicated Flies in the…

Posted by Prof Dr – Ing Morris Riedel on Tuesday, December 1, 2020


ResearchGate:Good Job Morris!Paper reached 100 Reads:Automatic Object Detection using #DBSCAN for Counting Intoxicated Flies in the FLORIDA Assay #HPC #clustering #DataScience @DEEPprojects @fzj_jsc @fz_juelich @Haskoli_Islands @helmholtz_ai
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Full text: https://t.co/sAdwaL6DPy
. pic.twitter.com/JMLONXIJJz

— Morris Riedel (@MorrisRiedel) December 27, 2019






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ResearchGate: Good Job Morris! Paper reached 100 Reads: Automatic Object Detection using #DBSCAN for Counting Intoxicated Flies in the FLORIDA Assay – our studies with drunken vinegar flies as a useful genetic tool to study the mechanistic basis of behaviors associated with alcoholism – #HPC #clustering #DataScience DEEP Projects #julichsupercomputingcenter @forschungszentrum_juelich @the_effective_communicators @haskoli_islands @von_hi @helmholtz_de #AI . Full text: https://buff.ly/2ZpKSAr . see: https://twitter.com/MorrisRiedel/status/1210476515672121344 .

Ein Beitrag geteilt von Morris Riedel (@morrisriedel) am Dez 27, 2019 um 2:35 PST

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Contact

Juelich Supercomputing Centre
Email: m.riedel[at]fz-juelich.de
Phone: +49 2461 61 – 3653

University of Iceland
Email: morris[at]hi.is

ORCID iD iconhttps://orcid.org/0000-0003-1810-9330

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