… We briefly give an overview of the pLSA model in Section 2. Then in Section 3 we describe
the classification algorithm based on applying pLSA to images. Section 4 describes the …

… scene classification method based on the bag-of-visual-words (BoVW) representation in
combination with the unsupervised probabilistic latent semantic analysis (pLSA… The pLSA model …

… 5) LDA [78] is a generative topic model evolved from the pLSA with the main difference
that it adds a Dirichlet prior to describe the latent variable topic instead of the fixed Gaussian …

… In Section II, we describe the PTM, including pLSA and LDA. Section III provides details
about the proposed SAL-PTM for HSR imagery scene classification. A description of the data …

… [32] requires a manual classification of 60 K local patches from the … pLSA model in Section
2. Then, in Section 3, we describe the hybrid classification algorithm based on applying pLSA …

… approaches for scene classification for enabling the viewing and classifying objects or scene
around… The focus is based on the general overview of Scene Classification based on pLSA (…

… terms (BOV) paradigm for scene classification. MMI coclustering … Unlike probabilistic Latent
Semantic Analysis (pLSA), which … Moreover, in practice we have observed that pLSA needs a …

… In this paper, a multifeature PLSA scene classification method is proposed for HSRIs. In
MPLSA, multiple features, eg, the spectral, texture, and SIFT features, are utilized to depict the …

… novel scene classification method that represents a scene as a latent aspect distribution using
the probabilistic latent semantic analysis (pLSA… The proposed scene classification method …

… et al. use pLSA, to generate the compact representation. They argue that pLSA has the dual
… paper, to enable comparison to previous scene classification work. We will see that super…