Wavelet and adaptive neuro-fuzzy inference system conjunction model for groundwater level predicting in a coastal aquifer. Neural Comput Appl. 2015;26:1203–15. https://doi.org/10.1007/s00521-014-1794-7. Article Google Scholar Zare M, Koch M. Groundwater level fluctuations simulation and ...
At the same time, our model’s inference speed reaches 66 FPS, which can basically meet the requirements of real-time inference. While the substantial parameter count could restrict our model’s deployment on embedded and mobile platforms, its significant contribution to the domain of RS image ...
Vimal MN (2018) Adaptive neuro-fuzzy inference system for classification of the mammographic image using electromagnetism-like optimization. Int J Biomed Eng Technol 26(4):376–384 Google Scholar Xia B, Jian Z, Tao N (2019) An effective combined multivariate control chart based on support vecto...
learnt using dedicated transforms and their associated coefficients and in the second stage, all the representations are fused together using a fusing (common) transform and its associated coefficients to effectively capture correlation between the different sensor representations for deriving an inference. ...
The subdivision of the original metric into separate time-scale components containing its different temporal trends and patterns should benefit the detection, allowing for the application of simpler inference methods with improved results. In particular, a simple statistical-based outlier identification ...
This is an multilingual implementation ofMB-iSTFT-VITSto support conversion to various languages. MB-iSTFT-VITS showed 4.1 times faster inference time compared with original VITS! Preprocessed Japanese Single Speaker training material is provided withつくよみちゃんコーパス(tsukuyomi-chan corpus).You ...
No-inference image sharpness assessment based on wavelet transform and image saliency map 2016 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR), IEEE (2016), pp. 43-48 Google Scholar Zhu et al., 2015 Z. Zhu, S. Wang, C.E. Woodcock Improvement and expansion of th...
Signatures, Multi-state Statistical Inference. Ed- ited by A. Lisnianski and I. Frenkel. 79-95. London: Springer (2012).A. Lisnianski, Lz-transform for a discrete-state continuous-time markov pro- cess and its applications to multi-state system reliability. In: Recent advances in system...
Liu, H., Loh, P.C., Blaabjerg, F.: 'Sub-module Short Circuit Fault Diagnosis in Modular Multilevel Converter Based on Wavelet Transform and Adaptive Neuro Fuzzy Inference System', Electric Power Components and Systems, 2015, pp. 1080-1088....
learnt using dedicated transforms and their associated coefficients and in the second stage, all the representations are fused together using a fusing (common) transform and its associated coefficients to effectively capture correlation between the different sensor representations for deriving an inference. ...