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Author Juan A. Carvajal; Dennis G. Romero; Angel D. Sappa pdf  openurl
  Title Fine-tuning deep convolutional networks for lepidopterous genus recognition Type Journal Article
  Year 2017 Publication Lecture Notes in Computer Science Abbreviated Journal  
  Volume Vol. 10125 LNCS Issue Pages pp. 467-475  
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  Notes Approved no  
  Call Number gtsi @ user @ Serial 63  
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Author Milton Mendieta; F. Panchana; B. Andrade; B. Bayot; C. Vaca; Boris X. Vintimilla; Dennis G. Romero pdf  openurl
  Title Organ identification on shrimp histological images: A comparative study considering CNN and feature engineering. Type Conference Article
  Year 2018 Publication IEEE Ecuador Technical Chapters Meeting ETCM 2018. Cuenca, Ecuador Abbreviated Journal  
  Volume Issue Pages 1-6  
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  Abstract The identification of shrimp organs in biology using

histological images is a complex task. Shrimp histological images

poses a big challenge due to their texture and similarity among

classes. Image classification by using feature engineering and

convolutional neural networks (CNN) are suitable methods to

assist biologists when performing organ detection. This work

evaluates the Bag-of-Visual-Words (BOVW) and Pyramid-Bagof-

Words (PBOW) models for image classification leveraging big

data techniques; and transfer learning for the same classification

task by using a pre-trained CNN. A comparative analysis

of these two different techniques is performed, highlighting

the characteristics of both approaches on the shrimp organs

identification problem.
 
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  Call Number gtsi @ user @ Serial 87  
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Author Dennis G. Romero; A. F. Neto; T. F. Bastos; Boris X. Vintimilla pdf  openurl
  Title RWE patterns extraction for on-line human action recognition through window-based analysis of invariant moments Type Conference Article
  Year 2012 Publication 5th Workshop in applied Robotics and Automation (RoboControl) Abbreviated Journal  
  Volume Issue Pages  
  Keywords Human action recognition, Relative Wavelet Energy, Window-based temporal analysis.  
  Abstract This paper presents a method for on-line human action recognition on video sequences. An analysis based on Mahalanobis distance is performed to identify the “idle” state, which defines the beginning and end of the person movement, for posterior patterns extraction based on Relative Wavelet Energy from sequences of invariant moments.  
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  Language English Summary Language English Original Title  
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  Notes Approved no  
  Call Number cidis @ cidis @ Serial 23  
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Author Dennis G. Romero; A. F. Neto; T. F. Bastos; Boris X. Vintimilla pdf  url
openurl 
  Title An approach to automatic assistance in physiotherapy based on on-line movement identification. Type Conference Article
  Year 2012 Publication VI Andean Region International Conference – ANDESCON 2012 Abbreviated Journal  
  Volume Issue Pages  
  Keywords patient rehabilitation, patient treatment, statistical analysis  
  Abstract This paper describes a method for on-line movement identification, oriented to patient’s movement evaluation during physiotherapy. An analysis based on Mahalanobis distance between temporal windows is performed to identify the “idle/motion” state, which defines the beginning and end of the patient’s movement, for posterior patterns extraction based on Relative Wavelet Energy from sequences of invariant moments.  
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  Publisher IEEE Place of Publication Andean Region International Conference (ANDESCON), 2012 VI Editor  
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  Area Expedition (up) Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 24  
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