首页|Report Summarizes Robotics and Automation Study Findings from Polytechnic University Torino (Jist: Joint Image and Sequence Training for Sequential Visual Place Recognition)
Report Summarizes Robotics and Automation Study Findings from Polytechnic University Torino (Jist: Joint Image and Sequence Training for Sequential Visual Place Recognition)
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NETL
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IEEE
A new study on Robotics - Robotics and Automation is now available. According to news originating from Turin, Italy, by NewsRx correspondents, research stated, "Visual Place Recognition aims at recognizing previously visited places by relying on visual clues, and it is used in robotics applications for SLAM and localization. Since typically a mobile robot has access to a continuous stream of frames, this task is naturally cast as a sequence-to-sequence localization problem." Financial support for this research came from Consorzio Interuniversitario Nazionale per l#x0027;Informatica. Our news journalists obtained a quote from the research from Polytechnic University Torino, "Nevertheless, obtaining sequences of labelled data is much more expensive than collecting isolated images, which can be done in an automated way with little supervision. As a mitigation to this problem, we propose a novel Joint Image and Sequence Training (JIST) protocol that leverages large uncurated sets of images through a multi-task learning framework. With JIST we also introduce SeqGeM, an aggregation layer that revisits the popular GeM pooling to produce a single robust and compact embedding from a sequence of single-frame embeddings."
TurinItalyEuropeRobotics and AutomationRoboticsPolytechnic University Torino
NETL
NSTL
IEEE
