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  2. 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]

  3. List of datasets in computer vision and image processing

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

    Images, text Object recognition, scene recognition 2014 [15] [16] J. Xiao et al. ImageNet: Labeled object image database, used in the ImageNet Large Scale Visual Recognition Challenge: Labeled objects, bounding boxes, descriptive words, SIFT features 14,197,122 Images, text Object recognition, scene recognition 2009 (2014) [17] [18] [19] J ...

  4. Outline of object recognition - Wikipedia

    en.wikipedia.org/wiki/Outline_of_object_recognition

    Object recognition – technology in the field of computer vision for finding and identifying objects in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects may vary somewhat in different view points, in many different sizes and scales or even when they are translated or rotated.

  5. Pandemonium architecture - Wikipedia

    en.wikipedia.org/wiki/Pandemonium_architecture

    Pandemonium architecture is a theory in cognitive science that describes how visual images are processed by the brain. It has applications in artificial intelligence and pattern recognition. The theory was developed by the artificial intelligence pioneer Oliver Selfridge in 1959. It describes the process of object recognition as the exchange of ...

  6. ImageNet - Wikipedia

    en.wikipedia.org/wiki/ImageNet

    The ImageNet project is a large visual database designed for use in visual object recognition software research. More than 14 million [1] [2] images have been hand-annotated by the project to indicate what objects are pictured and in at least one million of the images, bounding boxes are also provided. [3]

  7. Bag-of-words model in computer vision - Wikipedia

    en.wikipedia.org/wiki/Bag-of-words_model_in...

    Take LDA for an example. To model natural scene images using LDA, an analogy is made with document analysis: the image category is mapped to the document category; the mixture proportion of themes maps the mixture proportion of topics; the theme index is mapped to topic index; the codeword is mapped to the word.

  8. This beginner-friendly Photoshop class is on sale for under £10

    www.aol.com/beginner-friendly-photoshop-class...

    TL;DR: The Photoshop Master: From Beginner to Photoshop Pro course is on sale for £8.45 as of June 7, saving you 94% on list price. Apps like Facetune, PicsArt, Quickshot, and VSCO seem to have ...

  9. Contextual image classification - Wikipedia

    en.wikipedia.org/wiki/Contextual_image...

    As the image illustrated below, if only a small portion of the image is shown, it is very difficult to tell what the image is about. Mouth. Even try another portion of the image, it is still difficult to classify the image. Left eye. However, if we increase the contextual of the image, then it makes more sense to recognize. Increased field of ...

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    what is object recognitionoutline of object recognition