Few-Shot Calibration of Low-Cost Air Pollution (PM$_{2.5}$) Sensors Using Meta Learning-Reference-Cited by-同舟云学术

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Few-Shot Calibration of Low-Cost Air Pollution (PM$_{2.5}$) Sensors Using Meta Learning

Published:2022-05 Issue:5 Volume:6 Page:1-4
ISSN:2475-1472
Container-title:IEEE Sensors Letters
language:
Short-container-title:IEEE Sens. Lett.

Author:

Yadav Kalpit¹^ORCID,Arora Vipul¹^ORCID,Kumar Mohit²^ORCID,Tripathi Sachchida Nand²^ORCID,Motghare Vidyanand Motiram³,Rajput Karansingh A.³

Affiliation:

1. Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, India

2. Centre for Environmental Science and Engineering, Indian Institute of Technology Kanpur, Kanpur, India

3. Maharashtra Pollution Control Board, Mumbai, India

Funder

Bloomberg Philanthropies

Maharashtra Pollution Control Board

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7782634/9761174/09760185.pdf?arnumber=9760185

Reference23 articles.

1. Meta-Transfer Learning for Few-Shot Learning

2. Meta-neural networks that learn by learning

3. Attribute based shared hidden layers for cross-language knowledge transfer

4. Domain Adaptation-Based Deep Calibration of Low-Cost PM₂.₅ Sensors

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3. GAMMA: A universal model for calibrating sensory data of multiple low-cost air monitoring devices;Engineering Applications of Artificial Intelligence;2024-02

4. Efficient MLTL Calibration Model for Monitoring the Real-Time Pollutant Emission from Brick Kiln Industry;Journal of Advances in Information Technology;2024

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