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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link="#0563C1" vlink="#954F72"><div class=WordSection1><p class=MsoNormal><b><span style='font-size:12.0pt;line-height:105%;font-family:"Times New Roman",serif'>Last call for the 2019 Short course on Autonomous Systems (self-driving cars), 26-27th August 2019, Aristotle University of Thessaloniki, Greece<o:p></o:p></span></b></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>Dear Autonomous Systems (cars) engineers, scientists and enthusiasts,<o:p></o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>you are welcomed to register in the short course on Autonomous Systems having focus on autonomous/self-driving cars. It will take place on 26-27/8/2019 at the Aristotle University of Thessaloniki, Thessaloniki, Greece.<o:p></o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>The short course consists of 16 1-hour lectures organized in two parts (one per day):<o:p></o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif;color:black'>Part A lectures provide an in-depth presentation to <b>autonomous systems imaging</b> and the relevant architectures as well as a solid background on the necessary topics of computer vision (Image acquisition, camera geometry, Stereo and Multiview imaging, Motion estimation, Mapping and Localization.) They also provide an overview of the State-of-the-Art on<b> autonomous car vision and real-time road infrastructure monitoring</b>. </span><span style='font-family:"Times New Roman",serif'><o:p></o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif;color:black'>Part B lectures provide an in-depth view of <b>machine learning</b> related topics (Introduction to neural networks, Multilayer NNs/backpropagation, Deep neural networks, Convolution NNs, Deep learning for target detection). They will also cover Deep NN computation optimization schemes based on parallel architectures, GPU programming, and fast convolution algorithms. Furthermore, deep learning for 2D target (e.g., car, pedestrian) detection, tracking and 3D target localization will be detailed. Finally, additional topics related to autonomous car technologies, mainly focusing on <b>car vision</b> will be presented, involving <b>road scene understanding and 3D road modeling</b>.</span><span style='font-family:"Times New Roman",serif'><o:p></o:p></span></p><p class=MsoNormal><b><span style='font-family:"Times New Roman",serif'>You can use the following link for course registration:<o:p></o:p></span></b></p><p class=MsoNormal><span class=MsoHyperlink><b><span style='font-family:"Times New Roman",serif'><a href="http://icarus.csd.auth.gr/dl-and-cv-for-autonomous-cars-2019/">http://icarus.csd.auth.gr/dl-and-cv-for-autonomous-cars-2019/</a></span></b></span><b><span style='font-family:"Times New Roman",serif'><o:p></o:p></span></b></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>The course is already very well populated with registrants from all over the world. For questions, please contact: Ioanna Koroni <<span class=MsoHyperlink><a href="mailto:koroniioanna@csd.auth.gr">koroniioanna@csd.auth.gr</a></span>> <o:p></o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>The short course is organized by Prof. I. Pitas, IEEE and EURASIP fellow, Chair of the IEEE SPS Autonomous Systems Initiative, Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab), Aristotle University of Thessaloniki, Greece, Coordinator of the European Horizon2020 R&D project Multidrone. He is ranked 249-top Computer Science and Electronics scientist internationally by Guide2research (2018).<o:p></o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>Dr. R. Fan, <span class=tadv-format-panel><span style='color:black'>Hong Kong University of Science and Technology (HKUST) </span></span>will overview work on self-driving cars, while also presenting progress in the <span style='color:black'>HKUST autonomous vehicle project.<o:p></o:p></span></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>AUTH is ranked 153/182 internationally in Computer Science/Engineering, respectively, in USNews ranking. <o:p></o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>Thessaloniki is a very pleasant city at the end of August, with vibrant night-life, very close to world class resorts in Chalkidiki peninsula. Aristotle University of Thessaloniki is the biggest University in Greece and in SE Europe. It is highly ranked internationally and its campus is at the city center. <o:p></o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>Relevant links:<o:p></o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>Prof. I. Pitas: <span class=MsoHyperlink><a href="https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el">https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el</a></span><o:p></o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>H2020 project Multidrone: <span class=MsoHyperlink><a href="https://multidrone.eu/">https://multidrone.eu/</a></span><o:p></o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'>3) AIIA Lab <span class=MsoHyperlink><a href="http://www.aiia.csd.auth.gr">www.aiia.csd.auth.gr</a></span><o:p></o:p></span></p><p class=MsoNormal><span style='font-family:"Times New Roman",serif'><o:p> </o:p></span></p><p class=MsoNormal style='text-align:justify'><b><span style='font-family:"Times New Roman",serif'>Course description<o:p></o:p></span></b></p><p><b>Part A (8 hours), Computer vision topic list<o:p></o:p></b></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>1. Introduction to autonomous systems imaging<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>2. Introduction in computer vision<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>3. Image acquisition, camera geometry<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>4. Stereo and Multiview imaging<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>5. Motion estimation<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>6. Mapping and localization<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>7. Introduction to autonomous car vision<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>8. Real-time road infrastructure monitoring <o:p></o:p></span></p><p><b>Part B (8 hours) Deep learning topic list<o:p></o:p></b></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>1. Introduction to neural networks. Perceptron, backpropagation<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>2. Deep neural networks. Convolutional NNs<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>3. Parallel GPU and multicore CPU architectures. GPU programming<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>4. Fast convolution algorithms<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>5. Deep learning for target detection<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>6. 2D Target tracking and 3D target localization<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>7. Road scene understanding<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>8. 3D road surface modelling<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p> </o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>Sincerely yours<o:p></o:p></span></p><p class=MsoNoSpacing><span style='font-size:11.0pt'>Prof. I. Pitas<o:p></o:p></span></p><p class=MsoNormal><o:p> </o:p></p></div></body></html>