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Titlebook: Applications of Computational Intelligence; 5th IEEE Colombian C Alvaro David Orjuela-Ca?ón,Jesus Lopez,Juan Carlos Conference proceedings

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發(fā)表于 2025-3-23 11:14:48 | 只看該作者
Mine Sato,Nobuo Sayanagi,Toru Yanagiharahe controller by looking for the best tuning parameter solutions. The parameters of each algorithm affect the searching mechanism in different ways, and these effects were tested in two simulated systems. Ant colony optimization is much better than other algorithms at finding the best answers to our problems.
12#
發(fā)表于 2025-3-23 13:58:06 | 只看該作者
13#
發(fā)表于 2025-3-23 20:44:44 | 只看該作者
Conference proceedings 2023 in Cali, Colombia during July 27–29, 2022..The 7 extended papers included in this book were carefully reviewed and selected from 38 submissions. They were organized in topical sections as follows: ?Design of a segmentation and classification system for seed detection based on pixel intensity thresh
14#
發(fā)表于 2025-3-24 01:20:59 | 只看該作者
1865-0929 ions. They were organized in topical sections as follows: ?Design of a segmentation and classification system for seed detection based on pixel intensity thresholds and convolutional neural networks..978-3-031-29782-3978-3-031-29783-0Series ISSN 1865-0929 Series E-ISSN 1865-0937
15#
發(fā)表于 2025-3-24 05:10:41 | 只看該作者
https://doi.org/10.1007/978-3-031-00925-9orithms are illustrated by testing with real images, achieving an average accuracy of 92% in the selected set of classes. The experimental results verify that both algorithms can directly detect and classify the proposed set of seeds in input RGB images.
16#
發(fā)表于 2025-3-24 08:28:55 | 只看該作者
17#
發(fā)表于 2025-3-24 11:06:44 | 只看該作者
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發(fā)表于 2025-3-24 18:26:29 | 只看該作者
19#
發(fā)表于 2025-3-24 22:07:37 | 只看該作者
Communications in Computer and Information Sciencehttp://image.papertrans.cn/a/image/159335.jpg
20#
發(fā)表于 2025-3-25 01:52:23 | 只看該作者
https://doi.org/10.1007/978-3-031-00925-9on system of agricultural products to satisfy product quality requirements. This chapter employs artificial vision techniques to classify seeds in RGB images. As a first step, an algorithm based on pixel intensity threshold is developed to detect and classify a set of different seed types, such as r
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