9 citations · 39 across the 14 of their papers we have counts for
7 papers · 1 filter
Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clustering
Duy M. H. Nguyen, Hoang Nguyen, Mai T. N. Truong +7
Collecting large-scale medical datasets with fully annotated samples for training of deep networks is prohibitively expensive, especially for 3D volume data. Recent breakthroughs i…
Interactive Machine Learning for Image Captioning
Mareike Hartmann, Aliki Anagnostopoulou, Daniel Sonntag
We propose an approach for interactive learning for an image captioning model. As human feedback is expensive and modern neural network based approaches often require large amounts…
Self-Supervised Domain Adaptation for Diabetic Retinopathy Grading using Vessel Image Reconstruction
Duy M. H. Nguyen, Truong T. N. Mai, Ngoc T. T. Than +2
This paper investigates the problem of domain adaptation for diabetic retinopathy (DR) grading. We learn invariant target-domain features by defining a novel self-supervised task b…
Minimizing false negative rate in melanoma detection and providing insight into the causes of classification
Ellák Somfai, Benjámin Baffy, Kristian Fenech +8
Our goal is to bridge human and machine intelligence in melanoma detection. We develop a classification system exploiting a combination of visual pre-processing, deep learning, and…
A Competitive Deep Neural Network Approach for the ImageCLEFmed Caption 2020 Task
Marimuthu Kalimuthu, Fabrizio Nunnari, Daniel Sonntag
The aim of ImageCLEFmed Caption task is to develop a system that automatically labels radiology images with relevant medical concepts. We describe our Deep Neural Network (DNN) bas…
A categorisation and implementation of digital pen features for behaviour characterisation
Alexander Prange, Michael Barz, Daniel Sonntag
In this paper we provide a categorisation and implementation of digital ink features for behaviour characterisation. Based on four feature sets taken from literature, we provide a…