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We design and implement a HMM and run the HMM on alignment matrices for annotating duplicons.
Hmm, "on the verge of delivering"?
The influence of anisotropy, loss and dispersion of HMM on tunneling modes is discussed based on simulation results.
Hmm, on second thoughts.
The discrete HMM, on the other hand, reduces the feature space to a finite set of prototypes or representatives.
Liu and Chen proposed an adaptive Hidden Markov Model (HMM) on dynamic textures for video-based face recognition.
Switching ICA employs a hidden Markov model (HMM) on its model to represent whether the source is active or not.
Figure 19 Block diagram showing the scheme followed for making of recognition models using hmm on cellphone whispered speech data corpus.
For example, good results have been reported when using Hidden Markov Models (HMM) on rather specific classes of sound effects [7, 8].
Zihui Che Xueyun Ji [56] presented a new anomaly detection model based on rough set reduction and HMM on the basis of the analysis of shortcomings of other detection methods these days.
In Fig. 11 a, b, we show the ROCs generated by the discrete versions of the eHMM and the baseline HMM on dataset (mathfrak {D_{1}}), using EHD and Gabor features.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com