Search Results - "Prieto, F.A."

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  1. 1

    Fractographic classification in metallic materials by using computer vision by Bastidas-Rodriguez, M.X., Prieto-Ortiz, F.A., Espejo, Edgar

    Published in Engineering failure analysis (01-01-2016)
    “…The first step in the failure analysis is based on the visual inspection of the fracture surface. This is the base for the development of any fractographic…”
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    Journal Article
  2. 2

    Automatic fruit count on coffee branches using computer vision by Ramos, P.J., Prieto, F.A., Montoya, E.C., Oliveros, C.E.

    Published in Computers and electronics in agriculture (01-05-2017)
    “…•A system to count the number of fruits on a coffee branch in field conditions.•A technique that detects occluded and unoccluded fruits in field images.•A…”
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    Journal Article
  3. 3

    A system for classifying vegetative structures on coffee branches based on videos recorded in the field by a mobile device by Avendano, J., Ramos, P.J., Prieto, F.A.

    Published in Expert systems with applications (01-12-2017)
    “…•An expert system development to classify six coffee vegetative structures.•A non-destructive system based on a smartphone camera and computer vision…”
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    Journal Article
  4. 4

    On the application of digital image processing to surfaces of different nitride coatings by Riaño-Rojas, J.C., Restrepo-Parra, E., Prieto-Ortiz, F.A., Olaya-Florez, J.J.

    Published in Superlattices and microstructures (01-05-2008)
    “…In this work the application of different image processing techniques to low thickness coatings of CrN, NbN and TaN produced by unbalanced magnetron sputtering…”
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    Journal Article
  5. 5

    Segmentation and Extraction of Morphologic Features from Capillary Images by Riao-Rojas, J.C., Prieto-Ortiz, F.A., Morantes, L.J., Sanchez-Camperos, E., Jaramillo-Ayerbe, F.

    “…A methodology for segmentation and extraction morphologic feature from nailfold capillaroscopic images is presented. The main characteristic of the images…”
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    Conference Proceeding
  6. 6

    Location of coffee beans using Hopfield-type neural network by Arellano-Baez, D.R., Sanchez, E.N., Prieto-Ortiz, F.A.

    “…In this paper, recurrent (Hopfield-type) neural network associative memories are synthesized, using the perceptron algorithm, in order to locate coffee beans…”
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    Conference Proceeding