Given a poorly documented neural network model, we take the perspective ...
Researchers working on computational analysis of Whole Slide Images (WSI...
We use the Fortuin-Kasteleyn representation based improved estimator of ...
There are different multiple instance learning (MIL) pooling filters use...
Many machine learning adversarial attacks find adversarial samples of a
...
Motivation: High resolution 2D whole slide imaging provides rich informa...
Architecture, size, and shape of glands are most important patterns used...
A weakly supervised learning based clustering framework is proposed in t...
Adversarial attacks on convolutional neural networks (CNN) have gained
s...
Anomaly detection is a classical problem where the aim is to detect anom...
Different types of Convolutional Neural Networks (CNNs) have been applie...
While deep neural networks have achieved groundbreaking prediction resul...
We introduce our Distribution Regression Network (DRN) which performs
re...
We propose a flipped-Adversarial AutoEncoder (FAAE) that simultaneously
...