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In many computer-vision applications, computers are pre-programmed to solve a particular task, but methods based on learning are now becoming increasingly common. Examples of applications of computer vision include systems for: Learning 3D shapes has been a challenging task in computer vision.
Jiaya Jia has made outstanding contributions to computer vision technology, algorithms and engineering, and is among the world's leading experts in the field. His research partners include numerous renowned multinational technology companies, such as Microsoft , Qualcomm , Adobe , Intel , NVIDIA , Amazon , and Lenovo .
Region-based Convolutional Neural Networks (R-CNN) are a family of machine learning models for computer vision, and specifically object detection and localization. [1] The original goal of R-CNN was to take an input image and produce a set of bounding boxes as output, where each bounding box contains an object and also the category (e.g. car or ...
When a computer vision system or computer vision algorithm is designed the choice of feature representation can be a critical issue. In some cases, a higher level of detail in the description of a feature may be necessary for solving the problem, but this comes at the cost of having to deal with more data and more demanding processing.
The scale-invariant feature transform (SIFT) is a computer vision algorithm to detect, describe, and match local features in images, invented by David Lowe in 1999. [1] Applications include object recognition , robotic mapping and navigation, image stitching , 3D modeling , gesture recognition , video tracking , individual identification of ...
USC Iris computer vision conference list; Computer vision papers on the web A complete list of papers of the most relevant computer vision conferences. Computer Vision Online News, source code, datasets and job offers related to computer vision. Keith Price's Annotated Computer Vision Bibliography; CVonline Bob Fisher's Compendium of Computer ...
Correspondence is a fundamental problem in computer vision — influential computer vision researcher Takeo Kanade famously once said that the three fundamental problems of computer vision are: “Correspondence, correspondence, and correspondence!” [2] Indeed, correspondence is arguably the key building block in many related applications ...
Rick Szeliski (2010), Computer Vision: Algorithms and Applications, Springer. Computational Photography: Methods and Applications (Ed. Rastislav Lukac), CRC Press, 2010. Intelligent Image Processing (John Wiley and Sons book information). Comparametric Equations. GJB-1: Increasing the dynamic range of a digital camera by using the Wyckoff principle
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