Description

 3736
There are a variety of important applications that need to go beyond detecting individual objects within an image, and that instead need to segment the image into spatial regions of interest. An example of image segmentation involves medical imagery analysis, where it is often important to separate the pixels corresponding to different types of tissue, blood or abnormal cells, so that you can isolate a particular organ. Another example includes self-driving cars, where segmenting an image into distinct areas is needed to understand road scenes. In this lab, you will learn how to train and evaluate an image segmentation network using TensorFlow.
Lab Details
Tokens Required: 30 Tokens
Levels: Intermediate
Duration: 01 h:30 m
Access Time: 01 h:55 m
Setup Time: 00 h:05 m
Tags: Machine Learning, Deep Learning, TensorFlow, self-paced
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Reviews 832

  1. zhang qin
    It's only the simple clarifying about the way that how to use Tensorflow in image segementation. There is not enough reason why it works in that way.
    zhang qin Reviewed about 18 hours ago
  2. Anil Yuce

    Anil Yuce Reviewed 3 days ago
  3. Walid Ahmed

    Walid Ahmed Reviewed 3 days ago
  4. Jiri Kraus

    Jiri Kraus Reviewed 4 days ago
  5. Oren Haik

    Oren Haik Reviewed 5 days ago
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