Ara
Toplam kayıt 4, listelenen: 1-4
Block classical Gram-Schmidt-based block updating in low-rank matrix approximation
(Scientific Technical Research Council Turkey-Tubitak, 2018)
Low-rank matrix approximations have recently gained broad popularity in scientific computing areas. They are used to extract correlations and remove noise from matrix-structured data with limited loss of information. ...
Alternate Low-Rank Matrix Approximation in Latent Semantic Analysis
(Hindawi Ltd, 2019)
The latent semantic analysis (LSA) is a mathematical/statistical way of discovering hidden concepts between terms and documents or within a document collection (i.e., a large corpus of text). Each document of the corpus ...
Latent Semantic Analysis via Truncated ULV Decomposition
(Ieee, 2016)
Latent semantic analysis (LSA) usually uses the singular value decomposition (SVD) of the term-document matrix for discovering the latent relationships within the document collection. With the SVD, by disregarding the ...
Crop pest classification with a genetic algorithm-based weighted ensemble of deep convolutional neural networks
(ELSEVIER SCI LTD, 2020)
Insects are among the important causes of significant losses in crops such as rice, wheat, corn, soybeans, sugarcane, chickpeas, potatoes. Identification of insect species in the early period is crucial so that the necessary ...