id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_srlmqknhfna7jkf6u2ea4wgme4	Anant R. Bhatt	Cervical cancer detection in pap smear whole slide images using convNet with transfer learning and progressive resizing	2021	18	.pdf	application/pdf	7352	942	50	classification of cervical cells from Whole Slide Images (WSI) with optimum feature resizing, Convolution neural network, Sipakmed, Herlev, Metamorphic analysis, Deep learning propose a multi-class classification for single-cell and Whole Slide Images of cervical classification for whole slide images of the SIPaKMeD dataset, which helps in carrying Figure 3 Single cell Images from the Herlev Dataset, categorized into seven classes and shown as (A) superficial squamous epithelia, The VGG-19 model was trained on both the datasets to carry out binary and multi-class Table 1 The binary classification prediction scores for Herlev and SiPaKMeD Cervical Cancer Table 2 The multi-class prediction scores for the Herlev and SIPaKMeD Cervical Cancer datasets under evaluation criteria, that is, Accuracy, Cervical cancer detection in pap smear whole slide images using convNet with transfer learning and progressive resizing Cervical cancer detection in pap smear whole slide images using convNet with transfer learning and progressive resizing	./cache/work_srlmqknhfna7jkf6u2ea4wgme4.pdf	./txt/work_srlmqknhfna7jkf6u2ea4wgme4.txt