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</o:shapelayout></xml><![endif]--></head><body lang=EL link=blue vlink=purple style='word-wrap:break-word'><div class=WordSection1><div><div><div><div><div><div><div><div><p><b><span lang=EN-US style='font-size:13.5pt;font-family:"Georgia",serif'>Call for Papers: </span></b><span style='font-size:13.5pt;font-family:"Georgia",serif'><a href="https://avvision.xyz/icas21/" target="_blank"><span class=gmail-il><span lang=EN-US>ICAS</span></span><span lang=EN-US> 2021 Autonomous Vehicle Vision (AVVision) Special Session</span></a></span><span lang=EN-US style='font-size:13.5pt;font-family:"Georgia",serif'> (<b><span style='color:red'>Deadline extended to March 31, 2021</span></b>) </span><span lang=EN-US><o:p></o:p></span></p><p><span class=gmail-il><b><span style='font-size:13.5pt;font-family:"Georgia",serif'>ICAS</span></b></span><b><span style='font-size:13.5pt;font-family:"Georgia",serif'> is a flagship event sponsored by IEEE Signal Processing Society (SPS) through IEEE SPS Autonomous Systems Initiative.</span></b><o:p></o:p></p><p><b><span style='font-size:13.5pt;font-family:"Georgia",serif'>Special Session Website</span></b><span style='font-size:13.5pt;font-family:"Georgia",serif'>: <a href="https://avvision.xyz/icas21/" target="_blank">https://avvision.xyz/icas21/</a></span><o:p></o:p></p><p><span style='font-size:13.5pt;font-family:"Georgia",serif;color:#505050'>With a number of breakthroughs in autonomous system technology over the past decade, the race to commercialize self-driving cars has become fiercer than ever. The integration of advanced sensing, computer vision, signal/image processing, and machine/deep learning into autonomous vehicles enables them to perceive the environment intelligently and navigate safely. Autonomous driving is required to ensure safe, reliable, and efficient automated mobility in complex uncontrolled real-world environments. Various applications range from automated transportation and farming to public safety and environment exploration. Visual perception is a critical component of autonomous driving. Enabling technologies include: a) affordable sensors that can acquire useful data under varying environmental conditions, b) reliable simultaneous localization and mapping, c) machine learning that can effectively handle varying real-world conditions and unforeseen events, as well as “machine-learning friendly” signal processing to enable more effective classification and decision making, and d) resilient and robust platforms that can withstand adversarial attacks and failures. The </span><span style='font-size:13.5pt;font-family:"Georgia",serif'><a href="https://avvision.xyz/" target="_blank"><span style='color:darkgoldenrod;border:none windowtext 1.0pt;padding:0in'>Autonomous Vehicle Vision (AVVision)</span></a><span style='color:#505050'> Special Session at </span><a href="https://2021.ieee-icas.org/" target="_blank"><span style='color:darkgoldenrod;border:none windowtext 1.0pt;padding:0in'>the IEEE International Conference on Autonomous Systems 2021 (<span class=gmail-il>ICAS</span>'21)</span></a><span style='color:#505050'> will cover all these topics. Research papers are solicited in, but not limited to, the following topics:</span> </span><o:p></o:p></p><p><span style='font-size:13.5pt;font-family:"Arial",sans-serif;color:#505050'>• 3D road/environment reconstruction and understanding;<br>• Mapping and localization for autonomous cars;<br>• Semantic/instance driving scene segmentation and semantic mapping;<br>• Self-supervised/unsupervised visual environment perception;<br>• Car/pedestrian/object/obstacle detection/tracking and 3D localization;<br>• Car/license plate/road sign detection and recognition;<br>• Driver status monitoring and human-car interfaces;<br>• Deep/machine learning and image analysis for car perception;<br>• Adversarial domain adaptation for autonomous driving;<br>• On-board embedded visual perception systems;<br>• Bio-inspired vision sensing for car perception;<br>• Real-time deep learning inference.</span><o:p></o:p></p><p><b><span style='font-size:13.5pt;font-family:"Georgia",serif'>Organizers </span></b><o:p></o:p></p><p><span style='font-size:13.5pt;font-family:"Georgia",serif'>Dr. Rui Ranger Fan, UC San Diego</span><o:p></o:p></p><p><span style='font-size:13.5pt;font-family:"Georgia",serif'>Prof. Ioannis Pitas, Aristotle University of Thessaloniki</span><o:p></o:p></p><p><b><span style='font-size:13.5pt;font-family:"Georgia",serif'>Important Dates</span></b><o:p></o:p></p><p><span style='font-size:13.5pt;font-family:"Georgia",serif;color:#505050'>Full Paper Submission: 03/31/2021<br>Notification of Acceptance: 05/21/2021<br>Camera-Ready Paper Submission: 06/01/2021</span><span style='font-size:13.5pt;font-family:"Georgia",serif'> </span><o:p></o:p></p><p><b><span style='font-size:13.5pt;font-family:"Georgia",serif'>Submission</span></b><span style='font-size:13.5pt;font-family:"Georgia",serif'> </span><o:p></o:p></p><p><span style='font-size:13.5pt;font-family:"Georgia",serif;color:#505050'>Prospective authors are invited to submit full-length papers (up to 4 pages for technical content including figures and possible references, and with one additional optional 5th page containing only references) via the IEEE <span class=gmail-il>ICAS</span> 2021 conference website. Manuscripts should be original (not submitted/published anywhere else) and written in accordance with the standard double-column SPS IEEE conference format.<br><br>IEEE <span class=gmail-il>ICAS</span> 2021 requires that each accepted paper be presented by one of the authors in-person at the conference site according to the schedule to be published. Any paper accepted into the technical program, but not presented on-site will be withdrawn from the official proceedings archived on IEEE Xplore.</span><o:p></o:p></p><p><span style='font-size:13.5pt;font-family:"Georgia",serif;color:#505050'>More details can be found at </span><span style='font-size:13.5pt;font-family:"Georgia",serif'><a href="https://2021.ieee-icas.org/authors/call-papers" target="_blank">https://2021.ieee-<span class=gmail-il>icas</span>.org/authors/call-papers</a>.</span><o:p></o:p></p></div></div></div></div></div></div></div></div></div><div id="DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2"><br />
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