Using Autoencoders for Mammogram Compression

By Chun Chet Tan, Chikkannan Eswaran. 2011

38 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Francisco Herrera
2. Salvador Garcia
3. M. J. Jesús
4. Francisco Charte
5. Farzad Khalvati
6. Zehra Camlica
7. David Charte
8. Hamid R. Tizhoosh

In Computer Vision and Pattern Recognition

1. Salvador Garcia
2. Francisco Herrera
3. M. J. Jesús
4. Farzad Khalvati
5. Francisco Charte
6. Zehra Camlica
7. David Charte
8. Hamid R. Tizhoosh

Citations in the corpus

• A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines (2018, background): “This is the case of [121], where the performance of several AE models compressing mammogram image patches is analyzed.”
• Autoencoding the retrieval relevance of medical images (2015, background): “It investigates similar gray level regions in the image and count the number of pixels of these regions.”