When Deep Learning Meets Geometry for Air-to-Ground Perception on Drones
A special issue of Drones (ISSN 2504-446X).
Deadline for manuscript submissions: 30 August 2024 | Viewed by 18764
Special Issue Editors
Interests: devleoping air-to-ground sensing algorithms for drones (e.g. classification, detection, tracking, localization and mapping)
Special Issues, Collections and Topics in MDPI journals
Interests: optimization algorithms; computer vision; image processing; machine vision; pattern recognition; object recognition; feature extraction; 3D reconstruction; pattern matching; image recognition
Interests: visual tracking and machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recently, drones are drawing increasing attention as data acquisition or aerial perception platforms for many civilian or military applications. Owing to the success of deep learning in computer vision, drone images are processed in an end-to-end manner to achieve air-to-ground perception (e.g., detection, tracking, recognition). Generally, drone images are processed as general images ignoring the geometric metadata (e.g., location, altitude, pose) generated by the drone equipped GPS or IMU sensors. Inspired by Simultaneous Localization and Mapping (SLAM) which utilizes both image data and geometric data, this Special Issue aims at boosting deep learning based air-to-ground perception performance with geometric metadata for drones. We welcome submissions which provide the community with the most recent advancements regarding this Special Issue.
Topics of interest include, but are not limited to, the following:
- Air-to-ground object detection for drones
- Air-to-ground single/multiple object tracking for drones
- Air-to-ground object localization for drones
- Air-to-ground monocular visual slam for drones
Dr. Dongdong Li
Prof. Dr. Gongjian Wen
Dr. Yangliu Kuai
Dr. Runmin Cong
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- object detection
- object tracking
- object localization
- visual slam
- embeded vision on drones
