Connectionists: Call for paper abstracts for a EUSIPCO2021 Special Session proposal on 'Signal/image analysis and deep learning for drone-based infrastructure inspection and maintenance'

[Ioanna Koroni]

Dear Drone specialist,

we intend to submit the attached EUSIPCO2021 (https://eusipco2021.org/) special session proposal. 

If you work on such topics and you have high quality original research results, you are welcomed to send us a paper title, authors and 1-paragraph (1/2 page) abstract.
Abstracts will be peerly reviewed by third persons. The best 6 of them will be included in the special session proposal.

If the special session proposal is accepted, any relevant paper (certainly the ones included in the proposal plus more) will be invited through an open paper call (to come out then) to be submitted as a regular EUSIPCO special session paper and will be peerly reviewed as such.

Right now, we only need a paper title, author list and abstract, to be sent to us by email.
Please feel free to forward this to your students, as well as to other qualified labs you are in contact with.

As  the deadline is very close (22nd December 2020), I would greatly appreciate a fast contribution (till 22nd December 2020 9:00 am EET)

Best regards Merry Christmas and happy vacations I. Pitas

EUSIPCO2021 Special Session  proposal TITLE: Signal/image analysis and deep learning for drone-based infrastructure inspection and maintenance

DESCRIPTION
Automated inspection and maintenance of infrastructure is extremely important to many industries, promising simplified logistics, cost reductions, increased safety for human workers, quicker response times and more accurate results, when compared to traditional procedures. Drones are highly useful in this regard thanks to their easy deployment, their aerial point-of-view and their ability to access difficult-to-reach spaces. Recent advances in aerial robotics and AI have already pushed automated drone-based inspection and maintenance closer to reality, with manipulation, processing, analysis and learning of signals being at the forefront of this revolution. This special session will consider current research in this interdisciplinary subject, aiming to bring together researchers working on signals from the perspective of various fields, having in common an application focus on automated drone-based inspection and maintenance of any kind of infrastructure (e.g., roads/highways, electric towers/power lines, railway lines, pipelines, wind turbines, bridges, etc.). Topics of interest may include, among others:
Computer vision
Machine learning for signal processing
Localization and mapping
Multimodal perception
Sensor and data fusion
Human/drone interaction for cooperative maintenance Human intention prediction/modelling for cooperative maintenance Fault and anomaly detection Subcentimeter-accuracy inspection

NOVELTY AND MOTIVATION
This special session concerns a very timely topic with high industrial potential, given that fully/semi- automated drones are slowly emerging as a viable alternative to manually teleoperated ones for infrastructure inspection and maintenance applications, thanks to recent advances in robotics and AI. A lot of underlying cognitive functionalities that enable such autonomy, particularly the ones facilitating drone perception, rely on advanced signal analysis methods for achieving their goals, making this a topic of exceptional interest for the EUSIPCO community. Still, it is a highly interdisciplinary topic strongly interwoven with aerial robotics, thus justifying the need for a dedicated special session.

ORGANIZERS
Prof. Ioannis Pitas
(list to be completed soon)



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