Automatische Detektion von Trockenstress bei Tabakpflanzen mittels Machine-Learning-Verfahren.
Michael SiebersFranz UhrmannOliver ScholzChristoph StockerUte SchmidPublished in: GIL Jahrestagung (2016)
Keyphrases
- machine learning
- machine learning methods
- information extraction
- machine learning algorithms
- decision trees
- computer science
- pattern recognition
- learning tasks
- machine learning systems
- learning algorithm
- artificial intelligence
- data sets
- knowledge acquisition
- text mining
- computational biology
- machine learning approaches
- application of machine learning methods
- learning systems
- logic programs
- support vector machine
- computer vision
- natural language
- reinforcement learning
- explanation based learning
- machine learning and data mining
- data mining