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  2. Image segmentation - Wikipedia

    en.wikipedia.org/wiki/Image_segmentation

    Volume segmentation of a 3D-rendered CT scan of the thorax: ... Semantic segmentation is an approach detecting, for every pixel, the belonging class. [18]

  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. List of datasets in computer vision and image processing

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

    Segmentation, classification 2012 [107] [108] R. Bhatt. Bosphorus 3D Face image database. 34 action units and 6 expressions labeled; 24 facial landmarks labeled. 4652 Images, text Face recognition, classification 2008 [109] [110] A Savran et al. UOY 3D-Face neutral face, 5 expressions: anger, happiness, sadness, eyes closed, eyebrows raised ...

  5. CloudCompare - Wikipedia

    en.wikipedia.org/wiki/CloudCompare

    CloudCompare is a 3D point cloud processing software (such as those obtained with a laser scanner).It can also handle triangular meshes and calibrated images. Originally created during a collaboration between Telecom ParisTech and the R&D division of EDF, the CloudCompare project began in 2003 with the PhD of Daniel Girardeau-Montaut on Change detection on 3D geometric data. [2]

  6. Roberto Cipolla - Wikipedia

    en.wikipedia.org/wiki/Roberto_Cipolla

    Cipolla is known for his research contributions to the reconstruction, registration and recognition of three-dimensional objects from images. These include novel algorithms for the recovery of accurate 3D shape, visual localisation and tracking, and semantic segmentation and their practical application.

  7. Object detection - Wikipedia

    en.wikipedia.org/wiki/Object_detection

    Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]

  8. Region Based Convolutional Neural Networks - Wikipedia

    en.wikipedia.org/wiki/Region_Based_Convolutional...

    Given an image (or an image-like feature map), selective search (also called Hierarchical Grouping) first segments the image by the algorithm in (Felzenszwalb and Huttenlocher, 2004), [13] then performs the following: [2]

  9. Object co-segmentation - Wikipedia

    en.wikipedia.org/wiki/Object_co-segmentation

    Example video frames and their object co-segmentation annotations (ground truth) in the Noisy-ViDiSeg [1] dataset. Object segments are depicted by the red edge. In computer vision, object co-segmentation is a special case of image segmentation, which is defined as jointly segmenting semantically similar objects in multiple images or video ...