Evolution of LiverNet 2. x: Architectures for automated liver cancer grade classification from H&E stained liver histopathological images
AK Chanchal, S Lal, D Barnwal, P Sinha… - Multimedia Tools and …, 2024 - Springer
Recently, the automation of disease identification has been quite popular in the field of
medical diagnosis. The rise of Convolutional Neural Networks (CNNs) for training and …
medical diagnosis. The rise of Convolutional Neural Networks (CNNs) for training and …
Deep learning approaches for breast cancer detection in histopathology images: A review
L Priya CV, B VG, V BR… - Cancer Biomarkers, 2024 - content.iospress.com
BACKGROUND: Breast cancer is one of the leading causes of death in women worldwide.
Histopathology analysis of breast tissue is an essential tool for diagnosing and staging …
Histopathology analysis of breast tissue is an essential tool for diagnosing and staging …
[PDF][PDF] SAMS-Net: Fusion of attention mechanism and multi-scale features network for tumor infiltrating lymphocytes segmentation
X Zhang, K Liu, K Zhang, X Li, Z Sun, B Wei - Math. Biosci. Eng, 2023 - aimspress.com
Automatic segmentation of tumor-infiltrating lymphocytes (TILs) from pathological images is
essential for the prognosis and treatment of cancer. Deep learning technology has achieved …
essential for the prognosis and treatment of cancer. Deep learning technology has achieved …
Effective Classification for Logs of Routers Based on MLP Neural Networks
BT Nguyen-Tat, DK Nguyen - 2023 15th International …, 2023 - ieeexplore.ieee.org
This article discusses the classification of abnormal log messages from Juniper routers.
Abnormal log messages reflect the unusual activities of these routers. Classifying abnormal …
Abnormal log messages reflect the unusual activities of these routers. Classifying abnormal …