Estimating cooling capacities from aerial images using convolutional neural networks-Reference-Cited by-同舟云学术

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Estimating cooling capacities from aerial images using convolutional neural networks

Published:2023-11 Issue: Volume:349 Page:121561
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Barth Florian,Schüppler Simon,Menberg Kathrin,Blum Philipp

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference63 articles.

1. The future of cooling: opportunities for energy-efficient air conditioning;IEA,2018

2. Energieeffizienz in der Industrie;Blesl,2017

3. Optimum design and operation of an HVAC cooling tower for energy and water conservation;García Cutillas;Energies.,2017

4. IEA, 2021. Cooling, IEA, Paris https://www.iea.org/reports/cooling (accessed 01.12.2021).

5. Hotmaps. Heating and Cooling outlook until 2050, EU-28 Update March 2019;Kranzl,2018

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1. Automated cooling tower detection through deep learning for Legionnaires’ disease outbreak investigations: a model development and validation study;The Lancet Digital Health;2024-07

2. Research on SF-YOLONet metal gear end-face defect detection method based on evolutionary algorithm optimization;2023-10-12

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