Discrimination of breast cancer with microcalcifications on mammography by deep learning
J Wang, X Yang, H Cai, W Tan, C **, L Li - Scientific reports, 2016 - nature.com
Microcalcification is an effective indicator of early breast cancer. To improve the diagnostic
accuracy of microcalcifications, this study evaluates the performance of deep learning-based …
accuracy of microcalcifications, this study evaluates the performance of deep learning-based …
[HTML][HTML] Machine learning for industry 4.0: a systematic review using deep learning-based topic modelling
Machine learning (ML) has a well-established reputation for successfully enabling
automation through its scalable predictive power. Industry 4.0 encapsulates a new stage of …
automation through its scalable predictive power. Industry 4.0 encapsulates a new stage of …
Technological evolution of image sensing designed by nanostructured materials
Imaging sensing holds a remarkable place in modern electronics and optoelectronics for the
complementary metal-oxide-semiconductor integration of high-speed optical …
complementary metal-oxide-semiconductor integration of high-speed optical …
Domain adaptation network for cross-scene classification
In this paper, we present a domain adaptation network to deal with classification scenarios
subjected to the data shift problem (ie, labeled and unlabeled images acquired with different …
subjected to the data shift problem (ie, labeled and unlabeled images acquired with different …
Using convolutional features and a sparse autoencoder for land-use scene classification
In this article, we propose a novel approach based on convolutional features and sparse
autoencoder (AE) for scene-level land-use (LU) classification. This approach starts by …
autoencoder (AE) for scene-level land-use (LU) classification. This approach starts by …