Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features
424
Zitationen
7
Autoren
2017
Jahr
Abstract
The framework proposed is a simple, efficient and effective system for histopathology image automatic analysis. We successfully transfer ImageNet knowledge as deep convolutional activation features to the classification and segmentation of histopathology images with little training data. CNN features are significantly more powerful than expert-designed features.
Ähnliche Arbeiten
A survey on deep learning in medical image analysis
2017 · 13.833 Zit.
Dermatologist-level classification of skin cancer with deep neural networks
2017 · 13.402 Zit.
A survey on Image Data Augmentation for Deep Learning
2019 · 11.991 Zit.
QuPath: Open source software for digital pathology image analysis
2017 · 8.339 Zit.
Radiomics: Images Are More than Pictures, They Are Data
2015 · 8.105 Zit.