{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,28]],"date-time":"2025-06-28T04:08:43Z","timestamp":1751083723827,"version":"3.41.0"},"reference-count":37,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,9,20]],"date-time":"2020-09-20T00:00:00Z","timestamp":1600560000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,9,20]],"date-time":"2020-09-20T00:00:00Z","timestamp":1600560000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,9,20]]},"DOI":"10.1109\/itsc45102.2020.9294222","type":"proceedings-article","created":{"date-parts":[[2020,12,24]],"date-time":"2020-12-24T23:14:55Z","timestamp":1608851695000},"page":"1-7","source":"Crossref","is-referenced-by-count":2,"title":["Efficient Occupancy Grid Mapping and Camera-LiDAR Fusion for Conditional Imitation Learning Driving"],"prefix":"10.1109","author":[{"given":"Hesham M.","family":"Eraqi","sequence":"first","affiliation":[{"name":"The American University in Cairo,Computer Science & Engineering department,Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed N.","family":"Moustafa","sequence":"additional","affiliation":[{"name":"The American University in Cairo,Computer Science & Engineering department,Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jens","family":"Honer","sequence":"additional","affiliation":[{"name":"Valeo.,Driving Assistance department"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2001.977219"},{"key":"ref32","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"The Journal of Machine Learning Research"},{"journal-title":"End-to-end multi-modal sensors fusion system for urban automated driving","year":"2018","author":"sobh","key":"ref31"},{"journal-title":"ALVINN An Autonomous Land Vehicle in a Neural Network","year":"1989","author":"pomerleau","key":"ref30"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.376"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569433"},{"journal-title":"Valeo Scala","year":"2020","key":"ref35"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/504729.504754"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/4125865"},{"key":"ref11","first-page":"251","article-title":"Reactive collision avoidance using evolutionary neural networks","author":"eraqi","year":"2016","journal-title":"Proceedings of the 8th International Joint Conference on Computational Intelligence Volume 1 ECTA (IJCCI 2016) INSTICC"},{"key":"ref12","article-title":"End-to-end deep learning for steering autonomous vehicles considering temporal dependencies","author":"eraqi","year":"2017","journal-title":"Machine Learning for Intelligent Transportation Systems Workshop in the 31st Conference on Neural Information Processing Systems (NIPS)"},{"journal-title":"Resource-saving map for a driver assistance system of a motor vehicle","year":"2017","author":"eraqi","key":"ref13"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913491297"},{"journal-title":"Carla autonomous driving challenge 2019 results","year":"2019","author":"german ros","key":"ref15"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2005.1570477"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065707001093"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460730"},{"key":"ref19","article-title":"Computer vision for autonomous vehicles: Problems, datasets and state-of-the-art","author":"janai","year":"2017","journal-title":"arXiv preprint arXiv 1704 05519"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1002\/rob.20258"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2019.8917149"},{"key":"ref27","first-page":"3","article-title":"Rectifier nonlinearities improve neural network acoustic models","volume":"30","author":"maas","year":"2013","journal-title":"Proc ICML"},{"key":"ref3","article-title":"End to end learning for self-driving cars","author":"bojarski","year":"2016","journal-title":"arXiv preprint arXiv 1604 07316"},{"key":"ref6","first-page":"2722","article-title":"Deepdriving: Learning affordance for direct perception in autonomous driving","author":"chen","year":"2015","journal-title":"Proceedings of the IEEE International Conference on Computer Vision"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICUAS.2014.6842355"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00895"},{"key":"ref8","article-title":"Carla: An open urban driving simulator","author":"dosovitskiy","year":"2017","journal-title":"arXiv preprint arXiv 1711 03938"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460487"},{"key":"ref2","article-title":"Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst","author":"bansal","year":"2018","journal-title":"arXiv preprint arXiv 1812 02588"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/2.30720"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/app9112341"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2018.11.012"},{"journal-title":"imgaug","year":"2020","author":"jung","key":"ref21"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-6670(17)32056-6"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2017.8317943"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.08.005"},{"key":"ref25","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Advances in neural information processing systems"}],"event":{"name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","start":{"date-parts":[[2020,9,20]]},"location":"Rhodes, Greece","end":{"date-parts":[[2020,9,23]]}},"container-title":["2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9294153\/9294168\/09294222.pdf?arnumber=9294222","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T17:44:39Z","timestamp":1751046279000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9294222\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,20]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/itsc45102.2020.9294222","relation":{},"subject":[],"published":{"date-parts":[[2020,9,20]]}}}