Research output per year
Research output per year
Project Details
Description
Improving the usability of machine learning in industrial inspection systems
| Status | Finished |
|---|---|
| Effective start/end date | 01.10.2013 → 30.09.2015 |
Fields of science
- 101013 Mathematical logic
- 101024 Probability theory
- 202027 Mechatronics
- 102019 Machine learning
- 603109 Logic
- 101 Mathematics
- 102001 Artificial intelligence
- 102003 Image processing
- 101027 Dynamical systems
- 102023 Supercomputing
- 101004 Biomathematics
- 101014 Numerical mathematics
- 102035 Data science
- 101028 Mathematical modelling
- 102009 Computer simulation
- 206003 Medical physics
- 206001 Biomedical engineering
- 101020 Technical mathematics
JKU Focus areas
- Digital Transformation
-
Explaining Classifier Decisions Linguistically for Stimulating and Improving Operators Labeling Behavior
Lughofer, E., Richter, R., Neissl, U., Heidl, W., Eitzinger, C. & Radauer, T., 2017, In: Information Sciences. 420, p. 16-36 21 p.Research output: Contribution to journal › Article › peer-review
-
Advanced Linguistic Explanations of Classifier Decisions for Operators' Annotation Support
Lughofer, E., Richter, R., Neissl, U., Heidl, W., Eitzinger, C. & Radauer, T., 2016, Proceedings of the IEEE Intelligent Systems Conference 2016. Sofia: IEEE Press, p. 421-432 12 p. (IEEE IS 2016).Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review
-
On Improving Performance of Surface Inspection Systems by On-line Active Learning and Flexible Classifier Updates
Weigl, E., Heidl, W., Lughofer, E., Radauer, T. & Eitzinger, C., 2016, In: Machine Vision and Applications. 27, 1, p. 103-127 25 p.Research output: Contribution to journal › Article › peer-review