Total contribution score and fuzzy entropy based two-stage selection of FC, ReLU and inverseReLU features of multiple convolution neural networks for erythrocytes detection. Banerjee, S. & Chaudhuri, S. S. IET Comput. Vis., 13(7):640-650, 2019.
Total contribution score and fuzzy entropy based two-stage selection of FC, ReLU and inverseReLU features of multiple convolution neural networks for erythrocytes detection. [link]Link  Total contribution score and fuzzy entropy based two-stage selection of FC, ReLU and inverseReLU features of multiple convolution neural networks for erythrocytes detection. [link]Paper  bibtex   
@article{journals/iet-cvi/BanerjeeC19,
  added-at = {2020-03-24T00:00:00.000+0100},
  author = {Banerjee, Sriparna and Chaudhuri, Sheli Sinha},
  biburl = {https://www.bibsonomy.org/bibtex/2dcad519270d48417d4a297f9148e74e9/dblp},
  ee = {https://doi.org/10.1049/iet-cvi.2018.5545},
  interhash = {851c2437978b1d3ce9a9e54c1484f46e},
  intrahash = {dcad519270d48417d4a297f9148e74e9},
  journal = {IET Comput. Vis.},
  keywords = {dblp},
  number = 7,
  pages = {640-650},
  timestamp = {2020-03-25T11:51:31.000+0100},
  title = {Total contribution score and fuzzy entropy based two-stage selection of FC, ReLU and inverseReLU features of multiple convolution neural networks for erythrocytes detection.},
  url = {http://dblp.uni-trier.de/db/journals/iet-cvi/iet-cvi13.html#BanerjeeC19},
  volume = 13,
  year = 2019
}

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