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A Convolutional Autoencoder-based method for learning and ranking personal daylighting preference
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DOI：10.1016/j.buildenv.2025.113595.png)
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Abstract
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• Novel method for leaning personal binary daylighting preference • Two-stage training method: feature extraction module and preference inference module • CAE-based feature extractor designed to monitor unseen luminance map characteristics • Inference module: classifying daylighting preference and estimating ordinal ranking
Keywords:
personal binary daylighting preference
two-stage training
CAE-based feature extractor
preference inference
ordinal ranking