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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. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    Berkeley Segmentation Data Set and Benchmarks 500 (BSDS500) 500 natural images, explicitly separated into disjoint train, validation and test subsets + benchmarking code. Based on BSDS300. Each image segmented by five different subjects on average. 500 Segmented images Contour detection and hierarchical image segmentation 2011 [11]

  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. 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 ...

  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. 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.

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    mail.aol.com

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  9. Kernel (image processing) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(image_processing)

    In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more.This is accomplished by doing a convolution between the kernel and an image.