He also suggested the current visual programming language, which allows the team to analyze image data from any biomedical problem. JIPipe has already been used for several studies, for example to ...

A good way to see where this article is headed is to take a look at the screenshot of a demo program in Figure 1. The demo begins by loading a 1,000-item subset of the 60,000-item MNIST training data.

To address this, this article proposes a new genetic programming-based EDL approach to data-efficient image classification. The new approach can automatically evolve variable-length models using many ...

In Insite (labelINg medical imageS usIng submodular funcTions and sEmi-supervised data programming) we apply informed subset selection to identify a small number of most representative or diverse ...

Final capstone that I worked on as part of the AI programming in Python nanodegree at Udacity ... The application trains a deep learning model on a data set of images, then uses tha trained model to ...

Here, you'll learn about the basic technologies required to develop Big Data analytics solutions and deploy them at scale. You'll spend some time with the concept of virtualization and you'll have an ...

An image file also includes metadata about the image data itself, such as: the height and width of the image - this defines how many rows and columns the pixels are to be arranged in the ...