Morris Riedel Publications

Publications – Overview

2017 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 [ DOI ] [ Juelich ] [ More ] 2016 Scientific Big Data Analytics by HPC Thomas Lippert, Daniel Mallmann, Morris Riedel Publication Series of the John von Neumann Institute for Computing (NIC) NIC Series 48, 417, ISBN 978-3-95806-109-5, pp. 1 – 10, 2016...

object detection 0

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 [ DOI ] [ Juelich ] 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...

Scientific Big Data Analytics by HPC

Scientific Big Data Analytics by HPC

Scientific Big Data Analytics by HPC Thomas Lippert, Daniel Mallmann, Morris Riedel Publication Series of the John von Neumann Institute for Computing (NIC) NIC Series 48, 417, ISBN 978-3-95806-109-5, pp. 1 – 10, 2016 [ PID ] [ Juelich ] Abstract: Storing, managing, sharing, curating and especially analyzing huge amounts of data face an immense visibility and importance in industry and economy as well as in science and research. Industry and economy exploit ’Big Data’ for predictive analysis, to increase the efficiency of infrastructures, customer segmentation, and tailored services. In science, Big Data allows for addressing problems with complexities that...

image classification 0

On Understanding Big Data Impacts in Remotely Sensed Image Classification Using Support Vector Machine Methods

On Understanding Big Data Impacts in Remotely Sensed Image Classification Using Support Vector Machine Methods Gabriele Cavallaro, Morris Riedel, Matthias Richerzhagen, Jon Atli Benediktsson, Antonio Plaza IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Issue 99, pp. 1-13, 2015 [ DOI ] [ Juelich ] Abstract: Owing to the recent development of sensor resolutions onboard different Earth observation platforms, remote sensing is an important source of information for mapping and monitoring natural and man-made land covers. Of particular importance is the increasing amounts of available hyperspectral data originating from airborne and satellite sensors such as AVIRIS,...