In this letter, the authors present a single-image super-resolution method based on introducing novel spectral normalization to convolution of deep residual network. Moreover, construct new block (RB) and assemble it in cascade form. The RB was restructured by spectrally normalized layers activated function. addition, allows introduced trained network update additional weights. Furthermore, min...

Relationships among traits were investigated on the genomic and residual levels using novel methodology. This included inference on these relationships via Bayesian networks and an assessment of the networks with structural equation models. The methodology employed three steps. First, a Bayesian multiple-trait Gaussian model was fitted to the data to decompose phenotypic values into their genom...

Speech emotion recognition (SER) technology is significant for human–computer interaction, and this paper studies the features modeling of SER. Mel-spectrogram introduced utilized as feature speech, theory extraction process mel-spectrogram are presented in detail. A deep residual shrinkage network with bi-directional gated recurrent unit (DRSN-BiGRU) proposed paper, which composed convolution ...