Zobrazeno 1 - 10
of 745
pro vyhledávání: '"One-Class Support Vector Machine"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 1410-1421 (2025)
Sugarcane is a significant crop in terms of annual biomass in the world. Timely and accurate mapping of sugarcane planting is important for food security and sustainability. However, accurately remote-sensing-based mapping sugarcane remains challengi
Externí odkaz:
https://doaj.org/article/331aa4fc10fd4aa5be48b2e60b8f9f42
Autor:
Wen Luo, Youxin Zhao
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract To address the problem of fault branch recognition in mine ventilation systems, a one-class classification algorithm is introduced to construct the MC-OCSVM ventilation system fault diagnosis model, which is integrated with multiple OCSVMs.
Externí odkaz:
https://doaj.org/article/a1643f7197aa4cb780662dd5c904875d
Autor:
Edmund Fosu Agyemang
Publikováno v:
Scientific African, Vol 26, Iss , Pp e02386- (2024)
This study presents a comprehensive evaluation of five prominent unsupervised machine learning anomaly detection algorithms: One-Class Support Vector Machine (One-Class SVM), One-Class SVM with Stochastic Gradient Descent (SGD), Isolation Forest (iFo
Externí odkaz:
https://doaj.org/article/aa6a3d4aa3194f3aac81cba8ab595940
Publikováno v:
Frontiers in Big Data, Vol 7 (2024)
IntroductionMulti-layer aggregation is key to the success of out-of-distribution (OOD) detection in deep neural networks. Moreover, in real-time systems, the efficiency of OOD detection is equally important as its effectiveness.MethodsWe propose a no
Externí odkaz:
https://doaj.org/article/76003df510e842b48be9d98cdab589b4
Publikováno v:
Sensors, Vol 24, Iss 23, p 7435 (2024)
A harmonic reducer is an important component of industrial robots. In practical applications, it is difficult to obtain enough anomaly data from error cases for the supervised training of models. Whether the information contained in regular features
Externí odkaz:
https://doaj.org/article/8515918a281145d2beca2aec985ef59b
Publikováno v:
水下无人系统学报, Vol 31, Iss 6, Pp 839-846 (2023)
In order to improve the detection accuracy of ship wake, this paper proposed a ship wake detection method based on a one-dimensional convolutional neural network (1DCNN). Firstly, the simulation data set was constructed by using the ship wake scatter
Externí odkaz:
https://doaj.org/article/9f3f0cd5d6d347bb908a2733f06beee0
Publikováno v:
Journal of Petroleum Exploration and Production Technology, Vol 14, Iss 1, Pp 343-363 (2023)
Abstract Anomalies in oil-producing wells can have detrimental financial implications, leading to production disruptions and increased maintenance costs. Machine learning techniques offer a promising solution for detecting and preventing such anomali
Externí odkaz:
https://doaj.org/article/7d44d819597d4de7ad5d731a7a1a9157
Publikováno v:
Remote Sensing, Vol 16, Iss 13, p 2401 (2024)
Sea surface target detection is a key stage in a typical target detection system and directly influences the performance of the whole system. As an effective discriminator, the one-class support vector machine (OCSVM) has been widely used in target d
Externí odkaz:
https://doaj.org/article/1eb4899158cf42c6866ef885aa2f4ee1
Publikováno v:
Jisuanji kexue, Vol 50, Iss 3, Pp 371-379 (2023)
With the rapid development of the Internet,the security of network equipment has received extensive attention.Aiming at the problems of that the existing network equipment anomaly detection technology is destructive and difficult to detect,the paper
Externí odkaz:
https://doaj.org/article/d0a6b37c020b44189a5a594081625c11