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  2. U-Net - Wikipedia

    en.wikipedia.org/wiki/U-Net

    U-Net is a convolutional neural network that was developed for image segmentation. [1] The network is based on a fully convolutional neural network [ 2 ] whose architecture was modified and extended to work with fewer training images and to yield more precise segmentation .

  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. SqueezeNet - Wikipedia

    en.wikipedia.org/wiki/SqueezeNet

    SqueezeNet is a deep neural network for image classification released in 2016. SqueezeNet was developed by researchers at DeepScale, University of California, Berkeley, and Stanford University. In designing SqueezeNet, the authors' goal was to create a smaller neural network with fewer parameters while achieving competitive accuracy.

  5. Graph cuts in computer vision - Wikipedia

    en.wikipedia.org/wiki/Graph_cuts_in_computer_vision

    As applied in the field of computer vision, graph cut optimization can be employed to efficiently solve a wide variety of low-level computer vision problems (early vision [1]), such as image smoothing, the stereo correspondence problem, image segmentation, object co-segmentation, and many other computer vision problems that can be formulated in terms of energy minimization.

  6. Segmentation-based object categorization - Wikipedia

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

    For image segmentation, the matrix W is typically sparse, with a number of nonzero entries (), so such a matrix-vector product takes () time. For high-resolution images, the second eigenvalue is often ill-conditioned , leading to slow convergence of iterative eigenvalue solvers, such as the Lanczos algorithm .

  7. Connected-component labeling - Wikipedia

    en.wikipedia.org/wiki/Connected-component_labeling

    In short, once the first pixel of a connected component is found, all the connected pixels of that connected component are labelled before going onto the next pixel in the image. This algorithm is part of Vincent and Soille's watershed segmentation algorithm, [11] other implementations also exist. [12]

  8. Massive Courts Backlog Could Slow Trump Deportation Plan - AOL

    www.aol.com/massive-courts-backlog-could-slow...

    Homan says deporting those people will be his priority too, but he intends to cast a wider net, putting people into removal proceedings who ICE finds but who don’t pose an immediate threat ...

  9. Category:Image segmentation - Wikipedia

    en.wikipedia.org/wiki/Category:Image_segmentation

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