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Reconstruction of electrical impedance tomography images using chaotic ring-topology particle swarm optimization and non-blind search.

, , , , and . SMC, page 2618-2623. IEEE, (2014)

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Reconstruction of electrical impedance tomography images using chaotic self-adaptive ring-topology differential evolution and genetic algorithms., , , and . SMC, page 2605-2610. IEEE, (2014)A methodology for classification of lesions in mammographies using Zernike Moments, ELM and SVM Neural Networks in a multi-kernel approach., , and . SMC, page 988-991. IEEE, (2014)A semi-supervised fuzzy GrowCut algorithm to segment and classify regions of interest of mammographic images., , and . CoRR, (2018)Reconstruction of electrical impedance tomography images using genetic algorithms and non-blind search., , , and . ISBI, page 153-156. IEEE, (2014)A Model for Diagnosis of Alzheimer's Disease Using Haralick Texture Features and Meta Feature Selection., , , and . MLDM (1), page 132-145. ibai Publishing, (2019)Reconstruction of electrical impedance tomography images using chaotic ring-topology particle swarm optimization and non-blind search., , , , and . SMC, page 2618-2623. IEEE, (2014)Early prediction of generalized infection in intensive care units from clinical data: a committee-based machine learning approach., , , , , , , , , and . LA-CCI, page 1-6. IEEE, (2022)Segmentation of Mammography by Applying Extreme Learning Machine in Tumor Detection., , , and . IDEAL, volume 7435 of Lecture Notes in Computer Science, page 92-100. Springer, (2012)Emotion Recognition to Support Personalized Therapy: An Approach Based on a Hybrid Architecture of CNN and Random Forest., , and . LA-CCI, page 1-6. IEEE, (2023)Evaluation of Alzheimer's disease by analysis of MR images using multilayer perceptrons and committee machines., , , and . Comput. Medical Imaging Graph., 32 (1): 17-21 (2008)