Learning Face Pareidolia via Global Feature Transfer
Convolutional Neural Networks learn different details of features across various layers, progressively extracting features from low-level aspects such as edges to high-level semantic concepts. In this work, we investigate which feature representations are more effective for pareidolic face detection...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11071290/ |
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