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 ...
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 ...
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. ...
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...
Finally, Section 4.5 provides a comparison of the inference time, parameters, and FLOPs. 4.1 Experimental settings The computer used in the experiment was configured with an Intel(R) Xeon(R) Platinum 8280L CPU @ 2.60 GHz, four NVIDIA GeForce RTX 3090 GPUs, 32GB of RAM, Python 3.9.1, and...
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. ...
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....
Multi-structure modelVariational Bayes inferenceRecent works have demonstrated that using a properly structured prior for model-based compressive sensing (CS), can improve the recovery performance. However, there exists the low prior utilisation in previous works. Therefore, in this study, we introduce...
First, by adopting a multi-scale relaxation scheme based on super coupling transform, the inference using sequential tree re-weighted message passing approach [2] is accelerated. Next, by taking advantage of a statistical shape prior for the matching, the results are regularized and constrained, ...
In order to solve these problems, we proposed a fusion method based on double-density dual-tree discrete wavelet transform, which is approximately shift invariant and has more sub-bands per scale for finer frequency decomposition, and fuzzy inference system for fusing wavelet coefficients. This new...