Analysing transfer learning efficacy with different feature sets for occupancy detection
E Omeragic, O Orhan, T Uzunovic… - 2023 XXIX …, 2023 - ieeexplore.ieee.org
E Omeragic, O Orhan, T Uzunovic, E Golubovic
2023 XXIX International Conference on Information, Communication …, 2023•ieeexplore.ieee.orgOccupancy detection is one of the key elements in improving the energy performance of
buildings. Due to their nature, occupancy detection models could be trained on old building
data and adapted to new buildings for faster onboarding. We explore and analyse the
transfer learning framework applied to occupancy detection. We use a combination of Long-
short Term Memory neural network and convolutional neural network architectures and test
the transfer learning framework on three datasets. The results show that the transferred …
buildings. Due to their nature, occupancy detection models could be trained on old building
data and adapted to new buildings for faster onboarding. We explore and analyse the
transfer learning framework applied to occupancy detection. We use a combination of Long-
short Term Memory neural network and convolutional neural network architectures and test
the transfer learning framework on three datasets. The results show that the transferred …
Occupancy detection is one of the key elements in improving the energy performance of buildings. Due to their nature, occupancy detection models could be trained on old building data and adapted to new buildings for faster onboarding. We explore and analyse the transfer learning framework applied to occupancy detection. We use a combination of Long-short Term Memory neural network and convolutional neural network architectures and test the transfer learning framework on three datasets. The results show that the transferred models perform better than non-transferred models in almost all metric and dataset combinations.
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