標題: Titlebook: Applications of Evolutionary Computation in Image Processing and Pattern Recognition; Erik Cuevas,Daniel Zaldívar,Marco Perez-Cisneros Boo [打印本頁] 作者: Iridescent 時間: 2025-3-21 16:09
書目名稱Applications of Evolutionary Computation in Image Processing and Pattern Recognition影響因子(影響力)
書目名稱Applications of Evolutionary Computation in Image Processing and Pattern Recognition影響因子(影響力)學科排名
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書目名稱Applications of Evolutionary Computation in Image Processing and Pattern Recognition網(wǎng)絡公開度學科排名
書目名稱Applications of Evolutionary Computation in Image Processing and Pattern Recognition被引頻次
書目名稱Applications of Evolutionary Computation in Image Processing and Pattern Recognition被引頻次學科排名
書目名稱Applications of Evolutionary Computation in Image Processing and Pattern Recognition年度引用
書目名稱Applications of Evolutionary Computation in Image Processing and Pattern Recognition年度引用學科排名
書目名稱Applications of Evolutionary Computation in Image Processing and Pattern Recognition讀者反饋
書目名稱Applications of Evolutionary Computation in Image Processing and Pattern Recognition讀者反饋學科排名
作者: Judicious 時間: 2025-3-21 20:37
Intelligent Systems Reference Libraryhttp://image.papertrans.cn/a/image/159408.jpg作者: 身心疲憊 時間: 2025-3-22 00:52
Applications of Evolutionary Computation in Image Processing and Pattern Recognition978-3-319-26462-2Series ISSN 1868-4394 Series E-ISSN 1868-4408 作者: 出汗 時間: 2025-3-22 06:18
ACE Inhibitors/Angiotensin Receptor Blockerste the consideration of evolutionary methods for solving optimization problems. The study of the optimization methods is conducted in such a way that it is clear the necessity of using evolutionary optimization methods for the solution of image processing and pattern recognition problems.作者: Offset 時間: 2025-3-22 08:45 作者: Esalate 時間: 2025-3-22 16:32 作者: 別炫耀 時間: 2025-3-22 18:51 作者: 男學院 時間: 2025-3-22 23:26 作者: mutineer 時間: 2025-3-23 04:29 作者: 埋葬 時間: 2025-3-23 07:18 作者: 橡子 時間: 2025-3-23 13:39 作者: Orgasm 時間: 2025-3-23 17:24 作者: 傲慢物 時間: 2025-3-23 20:04 作者: 允許 時間: 2025-3-23 23:34 作者: FLAG 時間: 2025-3-24 06:11
https://doi.org/10.1007/978-1-4419-5659-0orithms based on evolutionary principles have been successfully applied to image segmentation with interesting performances. However, most of them maintain two important limitations: (1) they frequently obtain sub-optimal results (misclassifications) as a consequence of an inappropriate balance betw作者: Palate 時間: 2025-3-24 07:39 作者: 感情 時間: 2025-3-24 11:19
978-3-319-37099-6Springer International Publishing Switzerland 2016作者: dapper 時間: 2025-3-24 17:38 作者: 欺騙世家 時間: 2025-3-24 22:48 作者: Flatus 時間: 2025-3-24 23:10
Introduction,te the consideration of evolutionary methods for solving optimization problems. The study of the optimization methods is conducted in such a way that it is clear the necessity of using evolutionary optimization methods for the solution of image processing and pattern recognition problems.作者: 赤字 時間: 2025-3-25 03:41
Image Segmentation Based on Differential Evolution Optimization,tion (DE) is a heuristic method for solving complex optimization problems, yielding promising results. DE is easy to use, keeps a simple structure and holds acceptable convergence properties and robustness. In this chapter, an automatic image multi-threshold approach based on differential evolution 作者: Cupping 時間: 2025-3-25 10:53 作者: 豪華 時間: 2025-3-25 13:43 作者: 有危險 時間: 2025-3-25 17:12
Template Matching by Using the States of Matter Algorithm,and remote sensing. The TM approach seeks the best possible resemblance between a sub-image, known as template, and its coincident region within a source image. TM has two critical aspects: similarity measurement and search strategy. The simplest available TM method finds the best possible coinciden作者: defuse 時間: 2025-3-25 20:39 作者: 入會 時間: 2025-3-26 03:06 作者: nominal 時間: 2025-3-26 06:40 作者: Chromatic 時間: 2025-3-26 11:01 作者: 人充滿活力 時間: 2025-3-26 14:05
Automatic Segmentation by Using an Algorithm Based on the Behavior of Locust Swarms,orithms based on evolutionary principles have been successfully applied to image segmentation with interesting performances. However, most of them maintain two important limitations: (1) they frequently obtain sub-optimal results (misclassifications) as a consequence of an inappropriate balance betw作者: Hypomania 時間: 2025-3-26 20:01 作者: enterprise 時間: 2025-3-26 22:31
Book 2016 community can learn the way in whichimage processing and pattern recognition problems can be translated into anoptimization task. The book has been structured so that each chapter can beread independently from the others. It can serve as reference book for studentsand researchers with basic knowled作者: 樂章 時間: 2025-3-27 01:31
1868-4394 be translated into anoptimization task. The book has been structured so that each chapter can beread independently from the others. It can serve as reference book for studentsand researchers with basic knowled978-3-319-37099-6978-3-319-26462-2Series ISSN 1868-4394 Series E-ISSN 1868-4408 作者: Benzodiazepines 時間: 2025-3-27 05:40
Image Segmentation Based on Differential Evolution Optimization, efficient but also does not require prior assumptions whatsoever about the image. The method is likely to be most useful for applications considering different and perhaps initially unknown image classes. Experimental results demonstrate the algorithm’s ability to perform automatic threshold select作者: 托人看管 時間: 2025-3-27 10:00 作者: 猛擊 時間: 2025-3-27 14:32 作者: alcoholism 時間: 2025-3-27 19:26 作者: 簡略 時間: 2025-3-27 22:43
Estimation of Multiple View Relations Considering Evolutionary Approaches,he case with classic RANSAC. The rules for the generation of candidate solutions (samples) are motivated by the behavior of the immunological system in human beings. As a result, the approach can substantially reduce the number of iterations but still preserves the robust capabilities of RANSAC. The作者: debris 時間: 2025-3-28 02:25 作者: adulterant 時間: 2025-3-28 07:36 作者: obstruct 時間: 2025-3-28 14:20 作者: Minikin 時間: 2025-3-28 18:30
Automatic Segmentation by Using an Algorithm Based on the Behavior of Locust Swarms,called Locust Search (LS), is based on the behavior of swarms of locusts. Different to the most of existent evolutionary algorithms, it explicitly avoids the concentration of individuals in the best positions, avoiding critical flaws such as the premature convergence to sub-optimal solutions and the作者: Suppository 時間: 2025-3-28 19:37 作者: 勛章 時間: 2025-3-29 01:14
Reference work 2011Latest editions by calculating only a fixed subset of search locations at the price of poor accuracy. In this chapter, an algorithm based on Artificial Bee Colony (ABC) optimization is presented to reduce the number of search locations in the BM process. In the algorithm, the computation of search locations is dr作者: Diaphragm 時間: 2025-3-29 06:39
Reference work 2011Latest editionf encoded candidate ellipses are evolved through the evolutionary algorithm so that the best candidates can be fitted into the actual ellipses within the image. Just after the optimization process ends, an analysis over the embedded memory is executed in order to find the best obtained solution (the作者: 女歌星 時間: 2025-3-29 10:25 作者: TERRA 時間: 2025-3-29 12:10
