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  2. Pulse-coupled networks - Wikipedia

    en.wikipedia.org/wiki/Pulse-coupled_networks

    The Eckhorn model provided a simple and effective tool for studying small mammal’s visual cortex, and was soon recognized as having significant application potential in image processing. In 1994, Johnson adapted the Eckhorn model to an image processing algorithm, calling this algorithm a pulse-coupled neural network.

  3. U-Net - Wikipedia

    en.wikipedia.org/wiki/U-Net

    U-Net was created by Olaf Ronneberger, Philipp Fischer, Thomas Brox in 2015 and reported in the paper "U-Net: Convolutional Networks for Biomedical Image Segmentation". [1] It is an improvement and development of FCN: Evan Shelhamer, Jonathan Long, Trevor Darrell (2014). "Fully convolutional networks for semantic segmentation". [2]

  4. Image segmentation - Wikipedia

    en.wikipedia.org/wiki/Image_segmentation

    In digital image processing and computer vision, image segmentation is the process of partitioning a digital image into multiple image segments, also known as image regions or image objects (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to ...

  5. GrowCut algorithm - Wikipedia

    en.wikipedia.org/wiki/GrowCut_algorithm

    GrowCut is an interactive segmentation algorithm. It uses Cellular Automaton as an image model. Automata evolution models segmentation process. Each cell of the automata has some label (in case of binary segmentation - 'object', 'background' and 'empty'). During automata evolution some cells capture their neighbours, replacing their labels.

  6. Minimum spanning tree-based segmentation - Wikipedia

    en.wikipedia.org/wiki/Minimum_spanning_tree...

    In 2017, Saglam and Baykan used Prim's sequential representation of minimum spanning tree and proposed a new cutting criterion for image segmentation. [7] They construct the MST with Prim's MST algorithm using the Fibonacci Heap data structure. The method achieves an important success on the test images in fast execution time.

  7. Segmentation-based object categorization - Wikipedia

    en.wikipedia.org/wiki/Segmentation-based_object...

    Given an image D containing an instance of a known object category, e.g. cows, the OBJ CUT algorithm computes a segmentation of the object, that is, it infers a set of labels m. Let m be a set of binary labels, and let Θ {\displaystyle \Theta } be a shape parameter( Θ {\displaystyle \Theta } is a shape prior on the labels from a layered ...

  8. Category:Image segmentation - Wikipedia

    en.wikipedia.org/wiki/Category:Image_segmentation

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Help; Learn to edit; Community portal; Recent changes; Upload file

  9. Insight Segmentation and Registration Toolkit - Wikipedia

    en.wikipedia.org/wiki/Insight_Segmentation_and...

    ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning ...