Machine-learning based feature selection for a non-invasive breathing change detection.
Juliana Alves PegoraroSophie LavaultNicolas WattiezThomas SimilowskiJésus Gonzalez-BermejoEtienne BirmeléPublished in: BioData Min. (2021)
Keyphrases
- change detection
- feature selection
- machine learning
- remote sensing images
- remote sensing
- support vector machine
- mutual information
- land cover change
- text classification
- model selection
- remote sensing imagery
- data streams
- satellite imagery
- remotely sensed
- remotely sensed images
- image registration
- feature space
- satellite images
- unsupervised learning
- pattern recognition
- feature extraction
- concept drift
- frame difference
- gamma distributions
- land cover
- shot change detection
- high quality
- computer vision
- remote sensing data
- supervised learning
- motion estimation
- data analysis
- data mining