Empirically Comparing Two Dimensionality Reduction Techniques - PCA and FFT: A Settlement Detection Case Study in the Gauteng Province of South Africa.
Trienko L. GroblerWaldo KleynhansBrian Paxton SalmonPublished in: IGARSS (2019)
Keyphrases
- dimensionality reduction
- south africa
- principal component analysis
- case study
- south african
- principal components
- information and communication technologies
- high dimensional
- high dimensional data
- linear discriminant analysis
- feature extraction
- low dimensional
- pattern recognition
- information technology
- dimensionality reduction methods
- detection algorithm
- lower dimensional
- fourier transform
- manifold learning
- high dimensionality
- principal components analysis
- feature selection
- linear dimensionality reduction
- real time
- feature space
- database
- kernel pca
- linear projection
- random projections
- reduced dimensionality
- higher education
- dimension reduction
- fast fourier transform
- computer vision
- data mining
- real world
- covariance matrix
- frequency domain
- low cost
- data points
- locally linear embedding
- principle component analysis
- artificial intelligence