Zobrazeno 1 - 10
of 346
pro vyhledávání: '"Algorithm performance"'
Publikováno v:
PeerJ Computer Science, Vol 10, p e2418 (2024)
The efficiency of machine learning (ML) algorithms plays a critical role in their deployment across various applications, particularly those with resource constraints or real-time requirements. This article presents a comprehensive framework for eval
Externí odkaz:
https://doaj.org/article/c6f3d8cfe0634aaf9dbfca9e60d8712c
Autor:
Jia He
Publikováno v:
Elektronika ir Elektrotechnika, Vol 30, Iss 3, Pp 83-93 (2024)
There are many instances of intellectual property rights violations due to the common usage of digital data on the Internet, including unauthorised use, copying, and theft of digital content. Intellectual property rights of digital photos must be uph
Externí odkaz:
https://doaj.org/article/920482c4ac344e918413059f72d68357
Autor:
Aula, Sirwan A. a, Rashid, Tarik A. b, ⁎
Publikováno v:
In Ain Shams Engineering Journal January 2025 16(1)
Autor:
Sarah Sabeeh, Israa S. Al-Furati
Publikováno v:
Misan Journal of Engineering Sciences, Vol 2, Iss 2, Pp 12-37 (2023)
Abstract: This paper presents a comprehensive analysis of the performance of the Genetic Algorithm Probabilistic Roadmap (GA-PRM) algorithm in both simulated and real-world robotic environments. The GA-PRM algorithm is a promising approach for robot
Externí odkaz:
https://doaj.org/article/419f5271408d45dfa9e1f379f01beb4a
Autor:
Balmelli, Carlo 2, Berthod, Delphine 3, Buetti, Niccolò 4, Harbarth, Stephan 4, Jent, Philipp 5, Marschall, Jonas 5, Sax, Hugo 6, Schlegel, Matthias 7, Schweiger, Alexander 8, Senn, Laurence 9, Sommerstein, Rami 10, Troillet, Nicolas 3, Tschudin-Sutter, Sarah 11, Vuichard Gysin, Danielle 12, Widmer, Andreas 11, Wolfensberger, Aline 6, Zingg, Walter 6, Mueller, Anna, Pfister, Marc, Faes Hesse, Mirjam
Publikováno v:
In Clinical Microbiology and Infection November 2024
Publikováno v:
Technologies, Vol 12, Iss 7, p 113 (2024)
The paper addresses the issue of classification machine learning algorithm performance based on a novel probabilistic confusion matrix concept. The paper develops a theoretical framework which associates the proposed confusion matrix and the resultin
Externí odkaz:
https://doaj.org/article/1dc39147cb35448986687e41630a87d1
Publikováno v:
Complex & Intelligent Systems, Vol 9, Iss 5, Pp 5251-5266 (2023)
Abstract Fitness landscape analysis devotes to characterizing different properties of optimization problems, such as evolvability, sharpness, and neutrality. Although several landscape features have been proposed, only a few of them can be used in pr
Externí odkaz:
https://doaj.org/article/74eeb66ca99e4353b949c6d710c62884
Akademický článek
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Akademický článek
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Publikováno v:
IEEE Access, Vol 10, Pp 116467-116472 (2022)
The Minimum Weighted Connected Vertex Cover problem (MWCVC) is to find a subset $F\subset V(G)$ with minimum weight in a node-weighted graph $G$ , such that when removing the set $F$ , the inducing graph of remaining vertices holds no edges, and the
Externí odkaz:
https://doaj.org/article/573643bdc12249ff81fbd6fb89d97819