Prof. Dr. - Ing. Morris Riedel

Morris Riedel DBSCAN 0

Research

DBSCAN

DBSCAN Parallel & Scalable DBSCAN Goetz, M., Bodenstein, C., Riedel, M.: HPDBSCAN – Highly Parallel DBSCAN, in conference proceedings of ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 2015), Machine Learning in HPC Environments (MLHPC 2015) Workshop, November 15-20, 2015, Austin, Texas, USA [ EVENT ] [ DOI ] [ JUSER ] [ RESEARCHGATE ] [ MORE ] Open source available: Download DBSCAN Applications Bodenstein, C., Goetz, M., Jansen, A., Scholz, H., Riedel, M.: Automatic Object Detection using DBSCAN for Counting Intoxicated Flies in the FLORIDA Assay, in conference proceedings of the 15th IEEE International Conference...

object detection 0

Publications

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

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 ] 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...

HPDBSCAN Highly Parallel DBSCAN 0

Publications

HPDBSCAN – Highly Parallel DBSCAN

HPDBSCAN – Highly Parallel DBSCAN Goetz, M., Bodenstein, C., Riedel, M.: HPDBSCAN – Highly Parallel DBSCAN, in conference proceedings of ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 2015), Machine Learning in HPC Environments (MLHPC 2015) Workshop, November 15-20, 2015, Austin, Texas, USA [ EVENT ] [ DOI ] [ JUSER ] [ RESEARCHGATE ] Abstract: Clustering algorithms in the field of data-mining are used to aggregate similar objects into common groups. One of the best-known of these algorithms is called DBSCAN. Its distinct design enables the search for an apriori unknown number of arbitrarily shaped...