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  Browse All Reviews > Computing Methodologies (I) > Image Processing And Computer Vision (I.4) > Digitization and Image Capture (I.4.1)  
 
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  1-10 of 42 Reviews about "Digitization and Image Capture (I.4.1)": Date Reviewed
   Understanding image representations by measuring their equivariance and equivalence
Lenc K., Vedaldi A. International Journal of Computer Vision 127(5): 456-476, 2019.  Type: Article

As the number of artificial intelligence (AI)-based systems that support key aspects of our life, including health and security, increases exponentially, the demand for explainable AI has reached a peak in recent years. In the field of...

Jun 17 2019
  A survey of virtual sample generation technology for face recognition
Li L., Peng Y., Qiu G., Sun Z., Liu S. Artificial Intelligence Review 50(1): 1-20, 2018.  Type: Article

Just as the authors state that “virtual sample generation technology belongs to the category of machine learning,” nobody ever has enough real data to train a face recognition model, and they need synthesized data. ...

Feb 7 2019
   A discriminatively learned CNN embedding for person reidentification
Zheng Z., Zheng L., Yang Y. ACM Transactions on Multimedia Computing, Communications, and Applications 14(1): 1-20, 2017.  Type: Article

For knowing whether the same person appears in two images (reidentification), one can either use identification models (that is, classifying the person to its identity) or verification models (that is, classifying whether both the imag...

May 4 2018
   Making beautiful deep-sky images: astrophotography with affordable equipment and software (2nd ed.)
Parker G., Springer International Publishing, New York, NY, 2016. 189 pp.  Type: Book (978-3-319463-15-5)

Many of us look at the night sky with wonder and amazement at its sheer immensity, an immensity that only grows as we use telescopic instruments to gather more light than we can see with the naked eye. A step beyond simple observing by...

Nov 22 2017
  The mathematics of medical imaging: a beginner’s guide (2nd ed.)
Feeman T., Springer International Publishing, New York, NY, 2015. 197 pp.  Type: Book (978-3-319226-64-4)

Medical imaging is a very important application area of advanced computational techniques. Without the use of up-to-date mathematical ideas and the corresponding algorithms, it would not be possible to convert the measurement data comi...

May 2 2016
  A new image retrieval model based on monogenic signal representation
Zeng Z., Song L., Zheng Q., Chi Y. Journal of Visual Communication and Image Representation 33(C): 85-93, 2015.  Type: Article

The directional monogenic binary pattern (DMBP), a new texture descriptor to improve the description of the structure and orientation of the texture in an image, which in turn will improve image retrieval results, is proposed in this p...

Apr 12 2016
   Center symmetric local binary co-occurrence pattern for texture, face and bio-medical image retrieval
Verma M., Raman B. Journal of Visual Communication and Image Representation 32(C): 224-236, 2015.  Type: Article

Content-based image retrieval (CBIR) is vital for organizing and querying large image sets in useful ways. The general approach is to provide an image, or an image description, and find images that “look like this one....

Dec 15 2015
  Exploring image binarization techniques
Chaki N., Shaikh S., Saeed K., Springer Publishing Company, Incorporated, New York, NY, 2014. 82 pp.  Type: Book (978-8-132219-06-4)

An important aspect of making the workplace efficient is accessing information contained within prior documents in an accurate manner. Typically, these documents have been stored over a number of years but are no longer available in an...

Mar 4 2015
  Fast communication: face-image retrieval based on singular values and potential-field representation
Jian M., Lam K. Signal Processing 1009-15, 2014.  Type: Article

The importance of face-image retrieval cannot be overemphasized. This paper presents a method for retrieving face images from a database. The method is based on singular value decomposition (SVD) and potential-field representation....

Oct 20 2014
  Learning group-based dictionaries for discriminative image representation
Lei H., Mei K., Zheng N., Dong P., Zhou N., Fan J. Pattern Recognition 47(2): 899-913, 2014.  Type: Article

Being able to correctly find and identify images based on either visual or language cues is an activity easily performed by humans. Unsupervised computing environments have yet to reach the same level of accuracy, as is evident from th...

May 27 2014
 
 
 
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