Web: http://arxiv.org/abs/2201.10489

Jan. 26, 2022, 2:11 a.m. | Gengchen Mai, Yao Xuan, Wenyun Zuo, Krzysztof Janowicz, Ni Lao

cs.LG updates on arXiv.org arxiv.org

Generating learning-friendly representations for points in a 2D space is a
fundamental and long-standing problem in machine learning. Recently,
multi-scale encoding schemes (such as Space2Vec) were proposed to directly
encode any point in 2D space as a high-dimensional vector, and has been
successfully applied to various (geo)spatial prediction tasks. However, a map
projection distortion problem rises when applying location encoding models to
large-scale real-world GPS coordinate datasets (e.g., species images taken all
over the world) - all current location encoding …

arxiv cv geospatial learning predictions scale

More from arxiv.org / cs.LG updates on arXiv.org

Data Analytics and Technical support Lead

@ Coupa Software, Inc. | Bogota, Colombia

Data Science Manager

@ Vectra | San Jose, CA

Data Analyst Sr

@ Capco | Brazil - Sao Paulo

Data Scientist (NLP)

@ Builder.ai | London, England, United Kingdom - Remote

Senior Data Analyst

@ BuildZoom | Scottsdale, AZ/ San Francisco, CA/ Remote

Senior Research Scientist, Speech Recognition

@ SoundHound Inc. | Toronto, Canada