Nov 15, 2023 · In this study, we analyze the prediction performance of three different transfer learning (TL) methods leveraging target room data jointly with data from other ...
Oct 2, 2024 · Indoor climate relies on specific conditions, including room properties as well as occupant behavior, which makes it necessary to collect ...
This repository provides source code and data used for the paper "Overcoming Data Scarcity through Transfer Learning in CO2-based Building Occupancy Detection".
Fingerprint. Dive into the research topics of 'Overcoming Data Scarcity through Transfer Learning in CO2-Based Building Occupancy Detection'.
“Overcoming Data Scarcity through Transfer Learning in CO2-Based Building Occupancy Detection.” In Proceedings of the 10th ACM International Conference on ...
This article provides an in-depth survey of the strategies used to analyze sensor data and determine occupancy.
Jul 11, 2024 · This study investigates the effectiveness of transfer learning (TL) for load forecasting in office buildings, with the aim of addressing data ...
Nov 2, 2017 · Here, we describe and compare three techniques for transfer learning: multi-task, difference, and explicit latent variable architectures.
Missing: CO2- Based Building Occupancy Detection.
Deep Learning for Building Occupancy Estimation Using Environmental Sensors · Overcoming Data Scarcity through Transfer Learning in CO2-Based Building Occupancy ...
The paper aims to predict and evaluate thermal comfort of occupants using learning-based approach for thermal comfort modeling, overcoming the problems of data ...