Improving Computer-Aided Cervical Cells Classification Using Transfer Learning Based Snapshot Ensemble
Cervical cells classification is a crucial component of computer-aided cervical cancer detection. Fine-grained classification is of great clinical importance when guiding clinical decisions on the diagnoses and treatment, which remains very challenging. Recently, convolutional neural networks (CNN)...
Main Authors: | Wen Chen, Xinyu Li, Liang Gao, Weiming Shen |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-10-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/10/20/7292 |
Similar Items
-
dropCyclic: Snapshot Ensemble Convolutional Neural Network Based on a New Learning Rate Schedule for Land Use Classification
by: Sangdaow Noppitak, et al.
Published: (2022-01-01) -
Deep Hyperspectral Shots: Deep Snap Smooth Wavelet Convolutional Neural Network Shots Ensemble for Hyperspectral Image Classification
by: Farhan Ullah, et al.
Published: (2024-01-01) -
An Application of Transfer Learning and Ensemble Learning Techniques for Cervical Histopathology Image Classification
by: Dan Xue, et al.
Published: (2020-01-01) -
Image Classification of Wheat Rust Based on Ensemble Learning
by: Qian Pan, et al.
Published: (2022-08-01) -
Network Intrusion Detection Algorithm Combined with Group Convolution Network and Snapshot Ensemble
by: Aili Wang, et al.
Published: (2021-09-01)