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Author (up) Patricia Suarez; Angel Sappa; Boris Vintimilla edit  doi
  Title Cross-Spectral Image Patch Similarity using Convolutional Neural Network Type Conference Article
  Year 2017 Publication IEEE International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics Abbreviated Journal  
  Volume Issue Pages  
  Abstract The ability to compare image regions (patches) has been the basis of many approaches to core computer vision problems, including object, texture and scene categorization. Hence, developing representations for image patches have been of interest in several works. The current work focuses on learning similarity between cross-spectral image patches with a 2 channel convolutional neural network (CNN) model. The proposed approach is an adaptation of a previous work, trying to obtain similar results than the state of the art but with a lowcost hardware. Hence, obtained results are compared with both
classical approaches, showing improvements, and a state of the art CNN based approach.
  Address San Sebastian; Spain; May 2017  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ECMSM  
  Notes ADAS Approved no  
  Call Number Admin @ si @ SSV2017a Serial 2916  
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