74 citations · 484 across the 31 of their papers we have counts for
31 papers
Bag of Visual Words (BoVW) with Deep Features -- Patch Classification Model for Limited Dataset of Breast Tumours
Suvidha Tripathi, Satish Kumar Singh, Lee Hwee Kuan
Currently, the computational complexity limits the training of high resolution gigapixel images using Convolutional Neural Networks. Therefore, such images are divided into patches…
Weakly-supervised learning on Schrodinger equation
Kenta Shiina, Hwee Kuan Lee, Yutaka Okabe +1
We propose a machine learning method to solve Schrodinger equations for a Hamiltonian that consists of an unperturbed Hamiltonian and a perturbation. We focus on the cases where th…
An End-to-End Breast Tumour Classification Model Using Context-Based Patch Modelling- A BiLSTM Approach for Image Classification
Suvidha Tripathi, Satish Kumar Singh, Hwee Kuan Lee
Researchers working on computational analysis of Whole Slide Images (WSIs) in histopathology have primarily resorted to patch-based modelling due to large resolution of each WSI. T…
Inverse Renormalization Group based on Image Super-Resolution using Deep Convolutional Networks
Kenta Shiina, Hiroyuki Mori, Yusuke Tomita +2
The inverse renormalization group is studied based on the image super-resolution using the deep convolutional neural networks. We consider the improved correlation configuration in…
Automated Deep Learning Analysis of Angiography Video Sequences for Coronary Artery Disease
Chengyang Zhou, Thao Vy Dinh, Heyi Kong +4
The evaluation of obstructions (stenosis) in coronary arteries is currently done by a physician's visual assessment of coronary angiography video sequences. It is laborious, and ca…
Machine-Learning Study using Improved Correlation Configuration and Application to Quantum Monte Carlo Simulation
Yusuke Tomita, Kenta Shiina, Yutaka Okabe +1
We use the Fortuin-Kasteleyn representation based improved estimator of the correlation configuration as an alternative to the ordinary correlation configuration in the machine-lea…