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Aged 32 during the events of Pattern Recognition, Cayce lives in New York City.Though named by her parents after Edgar Cayce, she pronounces her given name "Case". [4] She is a freelance marketing consultant, a coolhunter with an unusual intuitive sensitivity for branding, [5] manifested primarily in her physical aversion to particular logos and corporate mascots. [6]
Pattern Recognition is a novel by science fiction writer William Gibson published in 2003. Set in August and September 2002, the story follows Cayce Pollard , a 32-year-old marketing consultant who has a psychological sensitivity to corporate symbols.
Semantic memory, which is used implicitly and subconsciously, is the main type of memory involved in recognition. [2] Pattern recognition is crucial not only to humans, but also to other animals. Even koalas, which possess less-developed thinking abilities, use pattern recognition to find and consume eucalyptus leaves. The human brain has ...
[9] [10] The last two examples form the subtopic image analysis of pattern recognition that deals with digital images as input to pattern recognition systems. [11] [12] Optical character recognition is an example of the application of a pattern classifier. The method of signing one's name was captured with stylus and overlay starting in 1990.
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]
In addition to designing a system for automated face recognition using eigenfaces, they showed a way of calculating the eigenvectors of a covariance matrix such that computers of the time could perform eigen-decomposition on a large number of face images. Face images usually occupy a high-dimensional space and conventional principal component ...
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Three-dimensional face recognition (3D face recognition) is a modality of facial recognition methods in which the three-dimensional geometry of the human face is used. It has been shown that 3D face recognition methods can achieve significantly higher accuracy than their 2D counterparts, rivaling fingerprint recognition .