Network dissection: quantifying interpretability of deep visual representations
We propose a general framework called Network Dissection for quantifying the interpretability of latent representations of CNNs by evaluating the alignment between individual hidden units and a set of semantic concepts. Given any CNN model, the proposed method draws on a broad data set of visual con...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020
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| Online Access: | https://hdl.handle.net/1721.1/124985 |