Copyright
©The Author(s) 2022.
World J Gastrointest Endosc. May 16, 2022; 14(5): 311-319
Published online May 16, 2022. doi: 10.4253/wjge.v14.i5.311
Published online May 16, 2022. doi: 10.4253/wjge.v14.i5.311
Figure 2 Methodological design of the study.
The proposed workflow encompasses selective collection of endoscopic images from the datasets, splitting and pre-processing of the data, iterative training of the classificatory model, and finally evaluation of its performance. DCNN: Dense convolutional neural network.
- Citation: Caires Silveira E, Santos Corrêa CF, Madureira Silva L, Almeida Santos B, Mattos Pretti S, Freire de Melo F. Recognition of esophagitis in endoscopic images using transfer learning. World J Gastrointest Endosc 2022; 14(5): 311-319
- URL: https://www.wjgnet.com/1948-5190/full/v14/i5/311.htm
- DOI: https://dx.doi.org/10.4253/wjge.v14.i5.311