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  Browse All Reviews > Computing Methodologies (I) > Pattern Recognition (I.5) > Applications (I.5.4) > Computer Vision (I.5.4...)  
 
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  1-10 of 212 Reviews about "Computer Vision (I.5.4...)": Date Reviewed
  What am I looking at? Low-power radio-optical beacons for in-view recognition on smart-glass
Ashok A., Xu C., Vu T., Gruteser M., Howard R., Zhang Y., Mandayam N., Yuan W., Dana K.  IEEE Transactions on Mobile Computing 15(12): 3185-3199, 2016. Type: Article

In order to justify their name, “smart glasses” need to recognize objects and determine their location in the user’s field of view. While different technologies can be used for object recognition and position estimation, in mobil...

Mar 31 2017
  Finding local leaf vein patterns for legume characterization and classification
Larese M., Granitto P.  Machine Vision and Applications 27(5): 709-720, 2016. Type: Article

Larese and Granitto essentially consider scale-invariant feature transform (SIFT) plus bag-of-words (BOW) plus support vector machines (SVM) to detect relevant vein patterns that characterize different species and varieties of legumes....

Mar 15 2017
  Artificial intelligence applications in information and communication technologies
Laalaoui Y., Bouguila N.,  Springer International Publishing, New York, NY, 2015. 213 pp. Type: Book (978-3-319198-32-3)

According to analysts, data volumes are expected to grow 44 fold in a decade (2011-2020). The variety of the data, along with the speed with which it is generated in an increasingly connected world, makes artificial intelligence (AI)-driven soluti...

Jul 8 2016
  Free-hand sketch recognition by multi-kernel feature learning
Li Y., Hospedales T., Song Y., Gong S.  Computer Vision and Image Understanding 137(C): 1-11, 2015. Type: Article

Touchscreen devices, or even electronic stylus writing instruments (for example, Apple Pencils), are becoming increasingly common nowadays. Drawing sketches is something humans have done to communicate since ancient times. Sketches can be used to ...

Oct 8 2015
  Reading the legends of Roman Republican coins
Kavelar A., Zambanini S., Kampel M.  Journal on Computing and Cultural Heritage 7(1): 1-20, 2014. Type: Article

If you Google “Republican Roman coins” you will be faced with thousands of fascinating images. There are three identifying features on most of them. Most show a head or object. Most have a mark identifying the mint. Most have a word kn...

Sep 14 2015
  Robust visual tracking via augmented kernel SVM
Bai Y., Tang M.  Image and Vision Computing 32(8): 465-475, 2014. Type: Article

Object tracking in videos (image sequences) is an important computer vision task with many different applications, including intelligent robots and vehicles, augmented reality, entertainment, scientific and industrial applications, and human-compu...

Mar 3 2015
  Advanced topics in computer vision
Farinella G., Battiato S., Cipolla R.,  Springer Publishing Company, Incorporated, New York, NY, 2013. 475 pp. Type: Book (978-1-447155-19-5)

Computer vision aims to make computers mimic humans in order to understand their environments through visual interpretation. This book is a collection of 14 papers covering a wide range of problems in computer vision. Very notably, these papers ar...

Jun 18 2014
  Decision forests for computer vision and medical image analysis
Criminisi A., Shotton J.,  Springer Publishing Company, Incorporated, New York, NY, 2013. 387 pp. Type: Book (978-1-447149-28-6)

Decision trees have proven useful for classification and regression, as well as other types of discrimination problems. A collection of decision trees, varying in specific ways related to their training data and/or configuration, is referred to as...

Mar 3 2014
  BabyTalk: understanding and generating simple image descriptions
Kulkarni G., Premraj V., Ordonez V., Dhar S., Li S., Choi Y., Berg A., Berg T.  IEEE Transactions on Pattern Analysis and Machine Intelligence 35(12): 2891-2903, 2013. Type: Article

Kulkarni et al. propose an automatic image description system based on predicted content using natural language statistics. They claim that the system is able to produce a correct description of an image in the form of natural language sentences, ...

Feb 13 2014
  Deep hierarchies in the primate visual cortex: What can we learn for computer vision?
Kruger N., Janssen P., Kalkan S., Lappe M., Leonardis A., Piater J., Rodriguez-Sanchez A., Wiskott L.  IEEE Transactions on Pattern Analysis and Machine Intelligence 35(8): 1847-1871, 2013. Type: Article

Understanding human vision processing has been the ultimate goal for many vision researchers, including machine vision developers. However, successes in specific problem domains such as face detection and gait recognition have driven the machine v...

Oct 23 2013
 
 
 
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