Deep neural networks (DNNs) are powerful tools for accurate predictions in various applications and have even shown to be superior to human experts in some domains, for instance for Melanoma detection.

Deep neural networks (DNNs) are powerful tools for accurate predictions in various applications and have even shown to be superior to human experts in some domains, for instance for Melanoma detection.

Deep neural networks (DNNs) are powerful tools for accurate predictions in various applications and have even shown to be superior to human experts in some domains, for instance for Melanoma detection.

This video offers a presentation of the iToBoS project, including its motivations, the challenges faced and the objectives.

Digital pathology is an emerging sub-division of conventional microscopy, enabling practitioners to virtualize glass pathology slides for more in-depth analysis.

Skin cancer is one of the most common types of all cancers. Melanoma may be the rarest subtype, but it will be responsible for over 7000 deaths this year, in the United States alone. Here’s the better news.

In the recent decade, deep neural networks (DNNs) have successfully been applied to a multitude of tasks both in research and industry.

Detecting overfitting is technically not possible unless we test the data.

Out of all the things that can go wrong with your ML model, overfitting is one of the most common and most detrimental errors.

Image relighting is the task of simulating a light source change in an image. It is an inverse challenging problem that is usually solved by estimating the image geometry, the reflectance and the lighting. Usually, the results contain artifacts that makes the output look unrealistic.