MaGamificationCNN

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Interactive Interface for Active Learning

Supervision: Shadi Albarqouni

Abstract

Tasks:

  • Implement a game for CNN Visualisation
  • Publish it online for crowdsourcing
  • Compare the results with few baselines

Requirements:

  • Good understanding of statistics and machine learning methods.
  • Very good programming skills in Unity3D, Java, and C++/Python

Location:

  • FMI Building, Garching

Literature

2016
S. Albarqouni, S. Matl, M. Baust, N. Navab, S. Demirci
Playsourcing: A Novel Concept for Knowledge Creation in Biomedical Research
Proceedings of MICCAI Workshop on Large-scale Annotation of Biomedical data and Expert Label Synthesis, Athens, Greece, October 2016
The first two authors contribute equally to this paper.
(bib)
S. Albarqouni, C. Baur, F. Achilles, V. Belagiannis, S. Demirci, N. Navab
AggNet: Deep Learning from Crowds for Mitosis Detection in Breast Cancer Histology Images
IEEE Transactions on Medical Imaging (TMI), Special Issue on Deep Learning, vol. 35, no. 5, pp. 1313 - 1321, 2016.
The first two authors contribute equally to this paper.
(bib)

ProjectForm
Title: Interactive Interface for Active Learning
Abstract:  
Student:  
Director: Prof. Nassir Navab
Supervisor: Shadi Albarqouni
Type: Project
Area: Machine Learning, Medical Imaging, Computer Vision
Status: draft
Start:  
Finish:  
Thesis (optional):  
Picture:  


Edit | Attach | Refresh | Diffs | More | Revision r1.7 - 22 Dec 2016 - 14:15 - ShadiAlbarqouni