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Predictive and discriminative localization of pathology using high resolution class activation maps with CNNs
PURPOSE: Existing class activation mapping (CAM) techniques extract the feature maps only from a single layer of the convolutional neural net (CNN), generally from the final layer and then interpolate to upsample to the original image resolution to locate the discriminative regions. Consequently the...
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| Pubblicato in: | PeerJ Comput Sci |
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| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
PeerJ Inc.
2021
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8293926/ https://ncbi.nlm.nih.gov/pubmed/34322593 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7717/peerj-cs.622 |
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