GeoAI2017: The First Workshop on AI and Deep Learning for Geographic Knowledge Discovery Redondo Beach, CA, United States, November 7, 2017 |
Conference website | https://udi.ornl.gov/geoai |
Submission link | https://easychair.org/conferences/?conf=geoai2017 |
Submission deadline | August 25, 2017 |
Dear colleagues,
It is our pleasure to invite you to contribute to The 1st Workshop on GeoAI: AI and Deep Learning for Geographic Knowledge Discovery, which will be held on Nov. 7, 2017 in Redondo Beach, California, USA.
Deep Learning and Artificial Intelligence (AI) techniques are transforming a range of sectors from computer vision and natural language processing to autonomous driving and healthcare. In particular, deep learning methods, also known as deep neural networks, achieve great success on many computer vision problems, with image classification and object detection as the prominent examples. This workshop will bring geoscientists, computer scientists, engineers, entrepreneurs, and decision makers from academia, industry, and government to discuss the latest trends, successes, challenges, and opportunities in the field of deep learning for geographical data mining and knowledge discovery. Through the workshop, attendees can exchange the latest techniques and workflows used in deep learning for geographical and spatial research. More details can be found on the workshop website: https://udi.ornl.gov/geoai
Example topics include but not limited to:
+ Novel deep neural network architectures and algorithms for geographic information analysis;
+ Deep learning for object extraction (such as roads, buildings) from remote sensing images;
+ Deep learning for geographic information extraction from text (e.g. social media, web documents, and news);
+ Deep learning models for multi/hyperspectral data analysis;
+ Deep learning methods for urban growth prediction;
+ AI and deep learning in autonomous transportation and high-precision maps;
+ Unsupervised learning
+ HPC architecture for deep learning
+ Applications of deep learning in disaster response
+ ...
Paper formats:
+ Full research paper: 8-10 pages
+ Short research paper or industry demo paper: 4 pages
+ Vision or statement paper: 2 pages
Important dates:
+ Paper submission: August 25, 2017
+ Acceptance decision: September 22, 2017
+ Camera ready version: October 6, 2017
+ Workshop date: November 7, 2017
Organizers:
General Chair: Huina Mao, Oak Ridge National Laboratory (maoh@ornl.gov)
General Co-Chair: Yingjie Hu, University of Tennessee Knoxville (yhu21@utk.edu)
General Co-Chair: Bandan Kar, Oak Ridge National Laboratory (karb@ornl.gov)
Program Chair: Song Gao, University of California Santa Barbara (sgao@geog.ucsb.edu)
Program Chair: Grant McKenzie, University of Maryland, College Park (gmck@umd.edu)
Program Committee:
Benjamin Adams, University of Canterbury
Andrea Ballatore, University of London, Birkbeck
Yao-Yi Chiang, University of Southern California, USA
Krzysztof Janowicz, University of California-Santa Barbara, USA
Brent Hecht, Northwestern University
Craig Knoblock, University of Southern California
Wenwen Li, Arizona State University
Xiaojiang Li, MIT Senseable City Lab
Yu Liu, Peking University, China
Shawn Newsam, University of California-Merced, USA
Roger Quo-Qian Wang, University of California-Berkeley, USA
William Wang, University of California-Santa Barbara, USA
Hsiuhan (Lexie) Yang, Oak Ridge National Laboratory,USA
Jiangye Yuan, Oak Ridge National Laboratory, USA
If you have any questions, please feel free to contact Yingjie Hu (yhu21@utk.edu) and Bandan Kar (karb@ornl.gov)
We look forward to seeing you in Redondo Beach!