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Experimenting with Deep Neural Networks for X-ray Image Segmentation

Sergey Kovalev


Deep neural networks present a great interest for the field of medical image segmentation. This article shares the results of the exploratory phase of the research aimed at examining the potential of deep learning methods and encoder-decoder convolutional neural networks for lung image segmentation. The study was conducted by our partners at the Biomedical Image Analysis Department of the United Institute of Informatics Problems, National Academy of Sciences of Belarus.



Using k-means Clustering in TensorFlow

Sergey Kovalev


The goal of this TensorFlow tutorial is to use the k-means algorithm for grouping data into clusters with similar characteristics. When working with k-means, the data in a training set does not need labels. As an unsupervised learning method, the algorithm builds clusters based on the data itself.



Using Linear Regression in TensorFlow

Sergey Kovalev


The linear regression algorithm helps to predict scores on the variable Y from the scores on the variable X. In this TensorFlow tutorial, we create a linear regression model and optimize it using the gradient descent method.



Visualizing TensorFlow Graphs with TensorBoard

Sergey Kovalev


TensorBoard helps engineers to analyze, visualize, and debug TensorFlow graphs. This tutorial will help you to get started with TensorBoard, demonstrating some of its capabilities.



Benchmarks and Research

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