Meal detection based on non-individualized moving horizon estimation and classification.
Konstanze KölleAnders Lyngvi FougnerØyvind StavdahlPublished in: CCTA (2017)
Keyphrases
- decision trees
- classification accuracy
- robust detection
- classification method
- detection algorithm
- object detection
- pattern recognition
- classification scheme
- classification process
- automatic classification
- image classification
- text classification
- false positives
- mammogram images
- classification systems
- detection accuracy
- machine learning
- orientation estimation
- classification rules
- feature extraction and classification
- classification algorithm
- anomaly detection
- model selection
- feature selection
- feature extraction
- feature vectors
- support vector machine
- microcalcification clusters
- joint detection
- neyman pearson
- real time
- statistical classification
- support vector machine classifier
- learning algorithm
- video sequences
- training set
- learning process
- support vector machine svm
- classification models
- density estimation
- automatic detection
- detection rate
- breast cancer
- dimensionality reduction
- decision rules
- learning styles
- training samples
- parameter estimation