Cargando…
Semantic Interpretation for Convolutional Neural Networks: What Makes a Cat a Cat?
The interpretability of deep neural networks has attracted increasing attention in recent years, and several methods have been created to interpret the “black box” model. Fundamental limitations remain, however, that impede the pace of understanding the networks, especially the extraction of underst...
Autores principales: | Xu, Hao, Chen, Yuntian, Zhang, Dongxiao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9762288/ https://www.ncbi.nlm.nih.gov/pubmed/36216585 http://dx.doi.org/10.1002/advs.202204723 |
Ejemplares similares
-
Semantic Interpretation for Convolutional Neural Networks: What Makes a Cat a Cat? (Adv. Sci. 35/2022)
por: Xu, Hao, et al.
Publicado: (2022) -
CAT-Site: Predicting Protein Binding Sites Using a Convolutional Neural Network
por: Petrovski, Žan Hafner, et al.
Publicado: (2022) -
CatStep: Automated Cataract Surgical Phase Classification and Boundary Segmentation Leveraging Inflated 3D-Convolutional Neural Network Architectures and BigCat
por: Mahmoud, Ossama, et al.
Publicado: (2023) -
Cat scratch disease: What to do with the cat?
por: Okrent Smolar, Avital Lily, et al.
Publicado: (2022) -
Analysis of Cataract Surgery Instrument Identification Performance of Convolutional and Recurrent Neural Network Ensembles Leveraging BigCat
por: Matton, Nicholas, et al.
Publicado: (2022)