{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T16:42:47Z","timestamp":1784133767325,"version":"3.55.0"},"reference-count":27,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,7]]},"DOI":"10.23919\/icif.2018.8455344","type":"proceedings-article","created":{"date-parts":[[2018,9,6]],"date-time":"2018-09-06T22:47:48Z","timestamp":1536274068000},"page":"2179-2186","source":"Crossref","is-referenced-by-count":162,"title":["Semantic Segmentation on Radar Point Clouds"],"prefix":"10.23919","author":[{"given":"Ole","family":"Schumann","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Markus","family":"Hahn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jurgen","family":"Dickmann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Wohler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/IRS.2015.7226281"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICMIM.2016.7533931"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICMIM.2017.7918863"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2017.7995871"},{"key":"ref14","first-page":"85","article-title":"Performance Analysis of Co-Located and Distributed MIMO Radar for Micro-Doppler Classification","author":"\u00f6zcan","year":"2016","journal-title":"EuRAD 2016"},{"key":"ref15","article-title":"Human RCS measurements and dummy requirements for the assessment of radar based active pedestrian safety systems","author":"schubert","year":"2013","journal-title":"14th International Radar Symposium (IRS)"},{"key":"ref16","first-page":"1","article-title":"Pedestrian recognition based on 24 GHz radar sensors","author":"heuel","year":"2010","journal-title":"11th International Radar Symposium (IRS)"},{"key":"ref17","first-page":"477","article-title":"Two-stage pedestrian classification in automotive radar systems","author":"heuel","year":"2011","journal-title":"12th International Radar Symposium (IRS)"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/IRS.2012.6233285"},{"key":"ref19","first-page":"1","article-title":"Radar frequency band invariant pedestrian classification","author":"molchanov","year":"2013","journal-title":"14th International Radar Symposium (IRS)"},{"key":"ref4","article-title":"PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation","author":"qi","year":"2017","journal-title":"Proc Computer Vision and Pattern Recognition (CVPR)"},{"key":"ref27","first-page":"2579","article-title":"Visualizing high-dimensional data using t-sne","volume":"9","author":"van der maaten","year":"2008","journal-title":"Journal of Machine Learning Research"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref6","author":"ronneberger","year":"2015","journal-title":"U-net Convolutional networks for biomedical image segmentation"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/SDF.2017.8126350"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.169"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref2","author":"badrinarayanan","year":"2015","journal-title":"Segnet A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation"},{"key":"ref9","article-title":"Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks","author":"ren","year":"2015","journal-title":"Neural Information Processing Systems (NIPS)"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref20","author":"qi","year":"2017","journal-title":"Pointnet++ Deep hierarchical feature learning on point sets in a metric space"},{"key":"ref22","first-page":"1","article-title":"Adam: a Method for Stochastic Optimization","author":"kingma","year":"2015","journal-title":"Proceedings of the 2015 International Conference on Learning Representations"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.170"},{"key":"ref24","first-page":"37","article-title":"Evaluation: From Precision, Recall and F-Measure to ROC, Informedness, Markedness & Correlation","volume":"2","author":"powers","year":"2007","journal-title":"Journal of Machine Learning Technologies"},{"key":"ref23","author":"qi","year":"2017","journal-title":"PointNet++ Tensorflow Implementation"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-37456-2_14"}],"event":{"name":"2018 21st International Conference on Information Fusion (FUSION 2018)","location":"Cambridge","start":{"date-parts":[[2018,7,10]]},"end":{"date-parts":[[2018,7,13]]}},"container-title":["2018 21st International Conference on Information Fusion (FUSION)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8442112\/8454975\/08455344.pdf?arnumber=8455344","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T11:23:54Z","timestamp":1643196234000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8455344\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":27,"URL":"https:\/\/doi.org\/10.23919\/icif.2018.8455344","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}