Journal: Scientific Reports

Article Title: A fuzzy rank-based ensemble of CNN models for classification of cervical cytology

doi: 10.1038/s41598-021-93783-8

Figure Lengend Snippet: Examples of images from the Mendeley LBC dataset . HSIL high squamous intra-epithelial lesion, LSIL low squamous intra-epithelial lesion, NIL negative for intra-epithelial lesion, SCC squamous cell carcinoma.

Article Snippet: No published work has been found on the Mendeley LBC dataset at the time of writing this manuscript for comparison.

Techniques:

Journal: Scientific Reports

Article Title: A fuzzy rank-based ensemble of CNN models for classification of cervical cytology

doi: 10.1038/s41598-021-93783-8

Figure Lengend Snippet: Visualization of the convolution filters of the Inception v3 model on the Mendeley LBC dataset (the plots have been formed using Keras framework of Python).

Article Snippet: No published work has been found on the Mendeley LBC dataset at the time of writing this manuscript for comparison.

Techniques:

Journal: Scientific Reports

Article Title: A fuzzy rank-based ensemble of CNN models for classification of cervical cytology

doi: 10.1038/s41598-021-93783-8

Figure Lengend Snippet: Loss curves obtained on fine-tuning the three CNN base learners: Inception v3, Xception and DenseNet-169 on the three datasets used in this research— (a–c) SIPaKMeD 2-class dataset, (d–f) SIPaKMeD 5-class dataset and (g–i) Mendeley LBC 4-class dataset (The loss curves have been plotted using Keras framework of Python).

Article Snippet: No published work has been found on the Mendeley LBC dataset at the time of writing this manuscript for comparison.

Techniques: