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An End-to-End Breast Tumour Classification Model Using Context-Based
  Patch Modelling- A BiLSTM Approach for Image Classification

An End-to-End Breast Tumour Classification Model Using Context-Based Patch Modelling- A BiLSTM Approach for Image Classification

5 June 2021
S. Tripathi
S. Singh
H. Lee
ArXivPDFHTML

Papers citing "An End-to-End Breast Tumour Classification Model Using Context-Based Patch Modelling- A BiLSTM Approach for Image Classification"

2 / 2 papers shown
Title
DPSeq: A Novel and Efficient Digital Pathology Classifier for Predicting
  Cancer Biomarkers using Sequencer Architecture
DPSeq: A Novel and Efficient Digital Pathology Classifier for Predicting Cancer Biomarkers using Sequencer Architecture
M. Cen
Xingyu Li
Bangwei Guo
J. Jonnagaddala
Hong Zhang
Xuesong Xu
MedIm
22
0
0
03 May 2023
Aggregated Residual Transformations for Deep Neural Networks
Aggregated Residual Transformations for Deep Neural Networks
Saining Xie
Ross B. Girshick
Piotr Dollár
Z. Tu
Kaiming He
297
10,216
0
16 Nov 2016
1