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Titlebook: Artificial Intelligence and Soft Computing; 20th International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2021

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31#
發(fā)表于 2025-3-26 21:34:06 | 只看該作者
32#
發(fā)表于 2025-3-27 02:31:43 | 只看該作者
Selecting the Optimal Configuration ofSwarm Algorithms for an NLP Task the optimal values for a set of parameters, based on a limited amount of training data. The starting point is a detailed analysis of generated solutions, which leads to a reformulation of the phrasing task. Based on this reformulation, the optimal swarm configuration is investigated, including the
33#
發(fā)表于 2025-3-27 07:11:09 | 只看該作者
Active Learning Strategies and Convolutional Neural Networks forMammogram Classificationome domains present a shortage of both samples and labels, for instance, the medical area. In this work, we propose machine learning approaches that include traditional supervised classifiers and active learning methods for the breast lesion domain, in order to aid breast cancer diagnosis. We propos
34#
發(fā)表于 2025-3-27 12:11:09 | 只看該作者
35#
發(fā)表于 2025-3-27 17:30:30 | 只看該作者
36#
發(fā)表于 2025-3-27 19:07:00 | 只看該作者
Constrained Clustering Problems: NewOptimization Algorithmsction, classification, systems’ misbehaviour, etc. In this paper, we focus on generalizing the K-Means clustering approach when involving linear constraints on the clusters’ size. Indeed, to avoid local optimum clustering solutions which consists in empty clusters or clusters with few points, we pro
37#
發(fā)表于 2025-3-28 00:46:33 | 只看該作者
Robustness of Supervised Learning Based on Combined CentroidsThe method is especially useful for localizing objects in images. Here, we extend the method to the task of joint localization of several objects in a?2D-image by means of combining several centroids. The novel approach, i.e. joint optimization of several centroids and a?subsequent optimization of t
38#
發(fā)表于 2025-3-28 04:55:59 | 只看該作者
39#
發(fā)表于 2025-3-28 08:55:17 | 只看該作者
40#
發(fā)表于 2025-3-28 12:16:41 | 只看該作者
Architecture Monitoring and Reliability Estimation Based on DIP Technologyication system more portable and integrated, estimates the crack more precisely and reduction in expenditure as well. The proposed algorithm accuracy is 93.8% as compared to the traditional and recent work.
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