Pattern Matching Algorithms
Pattern matching in computer vision refers to a set of computational techniques which enable the localization of a template pattern in a sample image or signal. Such template pattern can be a specific facial feature, an object of known characteristics or a speech pattern such as a word. Many of t...
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CVPR 2019
15-21 June in Long Beach, CA
RSIP Vision and CVPR will partner again to publish the CVPR Daily magazine for the 4th consecutive year. Meet us at CVPR 2019 to talk about your work! CVPR19 will take place on June 15-21 in Long Beach, California Read about CVPR 2016 Read about CVPR 2017 Read about CVPR 2018 Contact Us
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Extracting Features for Fingerprint Recognition and Matching
Fingerprint matching is used extensively in biometric identity verification for purposes ranging from forensic to recreational. The set of geometrical patterns, such as the ridges, whorls, and twists, enables to uniquely identify individuals (as far as we know): datasets of known fingerprints hav...
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ECCV 2018 – 8-14 September
in Munich, Germany
Meet us at ECCV to talk about your work and your presentation. September 8-14 in Munich, Germany. Contact Us Read about ECCV 2016 Read about ICCV 2017
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MICCAI 2018 – 16-20 September
in Granada, Spain
RSIP Vision and Computer Vision News will publish again the MICCAI Daily magazine, in partnership with MICCAI. Meet us at MICCAI to talk about your work and your presentation. September 16-20 in Granada, Spain. Contact Us Read about MICCAI 2016 Read about MICCAI 2017
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CVPR 2018
18-22 June – Salt Lake City, Utah
Computer Vision News (published by RSIP Vision) will partner again with CVPR to publish the CVPR Daily magazine. Meet us at CVPR to talk about your projects and work. June 18-22 in Salt Lake City, Utah. Contact Us Read about CVPR 2016 Read about CVPR 2017 Receive CVPR Daily in your mailbox
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MICCAI 2017
10-14 September in Quebec City, Canada
RSIP Vision shall publish once again the MICCAI Daily mag. Meet us at MICCAI to talk about your work September 10-14 in Quebec City, Canada Contact Us
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CVPR 2017
21-26 July in Honolulu, Hawaii
RSIP Vision shall publish once again the CVPR Daily mag. Meet us at CVPR to talk about your work July 21-26 in Honolulu, Hawaii Contact Us
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Pattern Recognition for Lens Markings Detection
Lens marking refers to the placement of temporary and/or permanent marking, semi-visible laser engraving for the use of lens identification and trademarks, and accurate placement of guiding lines along which lenses are cut. In the process of lens manufacturing, accurate placement and localization...
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Statistical pattern discovery in big data
The explosion of data collection techniques and resources is a known phenomenon of the current day and age. Human analysis of such large datasets is largely infeasible and the vast amount of information can only be dealt systematically and efficiently by algorithmic means. The so called ‘big data...
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Machine fault detection and classification
Automatic detection and diagnosis of various types of machine failure is a very interesting precess in industrial applications. With the advancement of sensors and machine intelligence, the reliability of automatic product inspection and fault detection is ever increasing. Monitoring the health o...
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Deformable pattern matching and classification
Three sources of apparent object deformation can occur: a change in the shape of the object itself, partial or full occlusion by dynamically changing background (other moving object or imaging conditions), or camera motion. Deforming objects are in general hard to track, owing to their unpredicta...
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3D object reconstruction by fringe projection
Fringe pattern projection for 3D object reconstruction has been around for 3 decades. The method finds its application in reconstructing static and dynamic objects in diverse fields such as biomedical, dentistry, circuit board inspection, virtual reality, vibration analysis, recreational 3D light...
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Type 2 interval fuzzy sets in pattern classification
In search for a pattern in an image, a video or a signal, one has to consider several sources of bias, noise and uncertainties. Such uncertainties are the result of acquisition of natural signals such as outdoors images in non-sterile and poorly lit conditions, possibly containing smear, blurs, a...
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Wafer defect detection by feature matching
Detection of microscopic defect in wafers and printed circuit boards is a standard procedure in the manufacturing process and also a crucial step in quality assurance. The time consuming human inspection of circuit boards has been replaced in nearly all production lines with an automatic in-line ...
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Animal Monitoring With Pattern Recognition
Automatic Identification of Pigs in a Pen Using Pattern Recognition The growing demand for animal products is characterized, at the farmer’s end, by an increased need for staff to manage and monitor the stock. It is estimated that by 2030 the world will experience a growth of 40% in the de...
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