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  2. List of datasets in computer vision and image processing

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

    Images, text Face recognition 2014 [99] [100] H. Ng et al. BioID Face Database Images of faces with eye positions marked. Manually set eye positions. 1521 Images, text Face recognition 2001 [101] [102] BioID Skin Segmentation Dataset Randomly sampled color values from face images. B, G, R, values extracted. 245,057 Text Segmentation ...

  3. Computer vision dazzle - Wikipedia

    en.wikipedia.org/wiki/Computer_vision_dazzle

    Computer vision dazzle, also known as CV dazzle, dazzle makeup, or anti-surveillance makeup, is a type of camouflage used to hamper facial recognition software, inspired by dazzle camouflage used by vehicles such as ships and planes.

  4. Intense pulsed light - Wikipedia

    en.wikipedia.org/wiki/Intense_pulsed_light

    Intense pulsed light (IPL) is a technology used by cosmetic and medical practitioners to perform various skin treatments for aesthetic and therapeutic purposes, including hair removal, photorejuvenation (e.g. the treatment of skin pigmentation, sun damage, and thread veins) as well as to alleviate dermatologic diseases such as acne.

  5. Fawkes (software) - Wikipedia

    en.wikipedia.org/wiki/Fawkes_(software)

    However, the efficacy of the software wanes if there are cloaked and uncloaked images that the facial recognition software can utilize. The image cloaking software has been tested on high-powered facial recognition software with varied results. [3] A similar facial cloaking software to Fawkes is called LowKey. LowKey also alters images on a ...

  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. FaceNet - Wikipedia

    en.wikipedia.org/wiki/FaceNet

    FaceNet is a facial recognition system developed by Florian Schroff, Dmitry Kalenichenko and James Philbina, a group of researchers affiliated with Google.The system was first presented at the 2015 IEEE Conference on Computer Vision and Pattern Recognition. [1]

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