DL-UAV19: Workshop on Deep-learning based computer vision for UAV in conjunction with CAIP 2019 Grand Hotel Salerno Salerno, Italy, September 6, 2019 |
Conference website | https://sites.google.com/view/dl-uav-caip-workshop/home |
Submission link | https://easychair.org/conferences/?conf=dluav19 |
Submission deadline | June 23, 2019 |
Unmanned aerial vehicles (UAV) or systems (UAS) offer an exciting and affordable means to capture aerial imagery for various application domains. With UAV based services set to be a 50 billion USD industry by 2023 and artificial intelligence rapidly gaining ground, intelligent UAV systems are to be the next disruptive technology. Indeed, some smart UAV already exist and soon the will become widespread thanks to recent advances in machine learning. Algorithms based on deep learning will undoubtedly play a crucial role in empowering application domains and services in the field of agriculture, remote sensing, urban and forest terrain modelling, construction, public safety, and crowd management. Photogrammetry and image stitching tools comprehensively capture terrain and landscapes to generate geographical maps that enable different kinds of UAV imagery analysis. The resolution and perspective angle at which terrains and objects are captured by an UAV, however, pose new challenges to the existing computer vision algorithms that are largely trained on conventional ground based imagery. There is therefore a new requirement to address the unique challenges posed by the use of intelligent algorithms either embedded on board of a UAV, or remotely controlling the movement and sensors mounted on the UAV to capture imagery for wireless transmission or post-flight processing.
The focus of this workshop is on topics related to deep learning, image processing and pattern recognition techniques for UAV applications. The main scope of this workshop is to identify and promote innovative deep-learning based methods capable of performing computer vision analysis unique to UAV imagery
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
- Full papers no longer than 8 pages must be submitted electronically through Springer LNCS Template. Each submission will be peer reviewed and this workshop follows single blind review process. At least one of the authors of each paper is required to register, attend, and present the paper at the workshop.
List of Topics
We welcome original and high-quality contributions on topics including, but not limited to:
- Computer vision applications
- Precision agriculture
- Livestock monitoring
- Scene understanding
- 3D rendering of buildings and archaeological sites
- Remote sensing
- Land surveying and mapping
- Target detection and object recognition
- Human /crowd tracking and recognition
- Surveillance
- Non-RGB vision sensors (InfraRed, multispectral, hyperspectral)
- Aerial object recognition
- On-board embedded vision
- 5G methods for remote monitoring and image analysis
Committees
Organizing committee
- Hamideh Kerdegari
- Manzoor Razaak
- Matthew Broadbent
Invited Speakers
Professor Peter Stütz
Title: Reconnaissance Sensor Automation in airborne Manned-Unmanned-Teaming Missions
Peter Stütz is Professor of Aeronautical Engineering at the University of the Bundeswehr Munich. His research interest focuses on sensor automation paradigms for unmanned aerial vehicles.
Publication
DL-UAV19 proceedings will be published in the Springer LNCS series.
Venue
The conference will be held in conjunction with The 18th international Conference on Computer Analysis of Images and Patterns, Salerno, Italy, September 6th, 2019
Contact
All questions about submissions should be emailed to Manzoor Razaak (manzoor.razaak@kingston.ac.uk) and Hamideh Kerdegari (h.kerdegari@kingston.ac.uk).