Web: http://arxiv.org/abs/2209.07581

Sept. 19, 2022, 1:11 a.m. | Guan-Han Huang, Alexei V. Dmitriev, Chia-Hsien Lin, Yu-Chi Chang, Mon-Chai Hsieh, Enkhtuya Tsogtbaatar, Merlin M. Mendoza, Hao-Wei Hsu, Yu-Chiang Lin,

cs.LG updates on arXiv.org arxiv.org

We train a deep learning artificial neural network model, Spatial Attention
U-Net to recover useful ionospheric signals from noisy ionogram data measured
by Hualien's Vertical Incidence Pulsed Ionospheric Radar. Our results show that
the model can well identify F2 layer ordinary and extraordinary modes (F2o,
F2x) and the combined signals of the E layer (ordinary and extraordinary modes
and sporadic Es). The model is also capable of identifying some signals that
were not labeled. The performance of the model can …

arxiv attention development extraction physics recovery space

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

Machine Learning Product Manager (Canada, Remote)

@ FreshBooks | Canada

Data Engineer

@ Amazon.com | Irvine, California, USA

Senior Autonomy Behavior II, Performance Assessment Engineer

@ Cruise LLC | San Francisco, CA

Senior Data Analytics Engineer

@ Intercom | Dublin, Ireland

Data Analyst Intern

@ ADDX | Singapore

Data Science Analyst - Consumer

@ Yelp | London, England, United Kingdom

Senior Data Analyst - Python+Hadoop

@ Capco | India - Bengaluru

DevOps Engineer, Data Team

@ SingleStore | Hyderabad, India

Software Engineer (Machine Learning, AI Platform)

@ Phaidra | Remote

Sr. UI/UX Designer - Artificial Intelligence (ID:1213)

@ Truelogic Software | Remote, anywhere in LATAM

Analytics Engineer

@ carwow | London, England, United Kingdom

HRIS Data Analyst

@ SecurityScorecard | Remote