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  2. 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]

  3. Image segmentation - Wikipedia

    en.wikipedia.org/wiki/Image_segmentation

    A fully automatic brain segmentation algorithm based on closely related ideas of multi-scale watersheds has been presented by Undeman and Lindeberg [76] and been extensively tested in brain databases. These ideas for multi-scale image segmentation by linking image structures over scales have also been picked up by Florack and Kuijper. [77]

  4. Alan Yuille - Wikipedia

    en.wikipedia.org/wiki/Alan_Yuille

    2017 with LC Chen, G Papandreou, I Kokkinos, K Murphy, Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs, in: IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 40, nº 4; 834-848.

  5. 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.

  6. 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 ...

  7. Otsu's method - Wikipedia

    en.wikipedia.org/wiki/Otsu's_method

    Iterative triclass thresholding algorithm is a variation of the Otsu’s method to circumvent this limitation. [15] Given an image, at the first iteration, the triclass thresholding algorithm calculates a threshold using the Otsu’s method.

  8. Random walker algorithm - Wikipedia

    en.wikipedia.org/wiki/Random_walker_algorithm

    The random walker algorithm is an algorithm for image segmentation. In the first description of the algorithm, [1] a user interactively labels a small number of pixels with known labels (called seeds), e.g., "object" and "background". The unlabeled pixels are each imagined to release a random walker, and the probability is computed that each ...

  9. Semantic analysis (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Semantic_analysis_(machine...

    In machine learning, semantic analysis of a text corpus is the task of building structures that approximate concepts from a large set of documents. It generally does not involve prior semantic understanding of the documents. Semantic analysis strategies include: Metalanguages based on first-order logic, which can analyze the speech of humans.