Titlebook: Soft Computing: Biomedical and Related Applications; Nguyen Hoang Phuong,Vladik Kreinovich Book 2021 The Editor(s) (if applicable) and The

lanugo

Optimization Under Fuzzy Constraints: Need to Go Beyond Bellman-Zadeh Approach and How It Is Related970s paper by Richard Bellman and Lotfi Zadeh, but these formulas have a limitation: small changes in the corresponding degrees can lead to a drastic change in the resulting selection. In this paper, we propose a natural modification of this formula, a modification that no longer has this limitation

敵意

Towards Parallel NSGA-II: An Island-Based Approach Using Fitness Redistribution Strategylexity and removes sharing parameter in comparing to other multiobjective evolutionary algorithms (MOEAs). Master-slave, island model and diffusion model are three approaches to parallel MOEAs. However, in those approaches, to ensure that the crossover operator is performing efficiently across sub-p

暫時(shí)中止

A Radial Basis Neural Network Approximation with Extended Precision for Solving Partial Differentialartial differential problems. RBFNs can be considered as a universal approximation scheme, and have emerged as a powerful approximation tool and become one of the main fields of research in the numerical analysis [.]. Derivative approximations of variable fields are computed through the radial basis

笨拙處理

Book 2021m agriculture, computer networks, economics and business, pavement engineering, politics, quantum computing, robotics, etc...This book helps practitioners and researchers to learn more about computational intelligence methods and their biomedical applications—and to further develop this important research direction..

B-cell

Attention U-Net with Active Contour Based Hybrid Loss for Brain Tumor Segmentation our approach and other approaches on a dataset of nearly 4000 brain MRI scans. Experiments demonstrate that the proposed method outperforms the state-of-the-art methods in terms of Dice coefficient and Jaccard indexes.

mighty

nominal

NEEDY

End-to-End Hand Rehabilitation System with Single-Shot Gesture Classification for Stroke Patientsas employed for hand detection and hand landmark extraction. A single-shot neural network model is proposed for hand gesture detection with an accuracy rate of 98%. Lastly, a visually interactive game was developed to promote engagement of the user during the performance of rehabilitation.

清真寺

modifier

Imbalance in Learning Chest X-Ray Images for COVID-19 DetectionSMOTE and SPY for class balancing. In recognition, the SVM is applied to classify images. The imbalance nature of the model with a solution combining VGG-16, SPY and SVM is demonstrated by excellent results over other parametric learning options.