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<div class="elementToProof"><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">Website:</span></div>
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<span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;"><a href="https://urldefense.com/v3/__https://aiforspace.github.io/2024/__;!!PAKc-5URQlI!4i1mhOggawAtjVTxu14ful_22XYhLBorSbR7Gt5s1qCPYWenL46OiBxwlqt8Zn3xp2-W6jL41p0XDxtfhtWuebHh770W1Yw$" target="_blank" id="OWAa6dc0637-6b65-bde0-4a51-d7e46f274bd3" class="OWAAutoLink" rel="noopener noreferrer" data-loopstyle="linkonly" data-linkindex="0" data-auth="NotApplicable" style="margin: 0px;">https://aiforspace.github.io/2024/</a></span></div>
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<div style="text-align: left; text-indent: 0px; margin: 0px;"><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">Call for Papers:</span></div>
<div style="text-align: left; text-indent: 0px; margin: 0px;"><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">We solicit papers for AI4Space. Papers will be reviewed and accepted papers will be published in the proceedings
of CVPR Workshops. Accepted papers will also be presented at the workshop, to be co-located with CVPR 2024 in Seattle.</span></div>
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<div style="text-align: left; text-indent: 0px; margin: 0px;"><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">The general emphasis of AI4Space is vision and learning algorithms for autonomous space systems, which operate
in the Earth’s orbital regions, cislunar orbit, planetary bodies (e.g., the moon, Mars and asteroids), and interplanetary space. Emphasis is also placed on novel sensors and processors for vision and learning in space, mitigating the challenges of the space
environment towards vision and learning (e.g., radiation, extreme temperatures), and fundamental difficulties in vision and learning for space (e.g., lack of training data, unknown operating environments).</span></div>
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<div style="text-align: left; text-indent: 0px; margin: 0px;"><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">A specific list of topics is as follows:</span></div>
<div style="text-align: left; text-indent: 0px; margin: 0px;"><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">- Vision and learning for spacecraft navigation and operations (e.g., rendezvous, proximity operations, docking,
space maneuvers, entry descent landing).</span></div>
<div style="text-align: left; text-indent: 0px; margin: 0px;"><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">- Vision and learning for space robots (e.g., rovers, UAVs, UGVs, UUWs) and multi-agent systems.</span></div>
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</span><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">Mapping and global positioning on planetary bodies (moon, Mars, asteroids), including celestial positioning.</span></div>
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</span><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">Onboard AI for Earth observation applications (e.g. near-real-time disaster monitoring, distributed learning on satellites, tip and cue satellite-based systems).</span></div>
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</span><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">Onboard AI for satellite operations (e.g. AI-based star trackers, fault detection isolation and recovery).</span></div>
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</span><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">Space debris monitoring and mitigation.</span></div>
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</span><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">Sensors for space applications (e.g., optical, multispectral, lidar, radar, neuromorphic).</span></div>
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</span><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">Onboard compute hardware for vision and learning (e.g., neural network accelerators, neuromorphic processors).</span></div>
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</span><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">Mitigating challenges of the space environment (e.g., radiation, thermal) to vision and learning systems.</span></div>
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</span><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">Datasets, transfer learning and domain gap.</span></div>
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<div style="text-align: left; text-indent: 0px; margin: 0px;"><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">Paper deadline:</span></div>
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<span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">8 March 2024</span></div>
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<div style="text-align: left; text-indent: 0px; margin: 0px;"><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">The workshop will also feature exciting Invited Seminars by Soon-Jo Chung (Caltech and JPL) and Gianluca Furano
(ESA).</span></div>
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<div style="text-align: left; text-indent: 0px; margin: 0px;"><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;">More details:</span></div>
<div style="text-align: left; text-indent: 0px; margin: 0px;"><span style="font-family: Arial, Helvetica, sans-serif; font-size: 11pt; color: black;"><a href="https://aiforspace.github.io/2024/" target="_blank" id="OWA9c8983ff-4a25-d586-ce35-6a59fd6f1402" class="OWAAutoLink" rel="noopener noreferrer" data-linkindex="1" data-loopstyle="linkonly" data-auth="NotApplicable" style="margin: 0px;">https://aiforspace.github.io/2024/</a></span></div>
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