Zobrazeno 1 - 10
of 2 014
pro vyhledávání: '"decision boundary"'
Autor:
Divya Rishi Shrivastava, Shahbaz Ahmed Siddiqui, Kusum Verma, S. Singh, Majed A. Alotaibi, Hasmat Malik, Mohammed E. Nassar
Publikováno v:
Energy Reports, Vol 11, Iss , Pp 895-907 (2024)
The performance of power networks is enhanced by the penetration of solar energy, which helps to equate continuously the generation and demand power imbalance. However, the time margin that grids must adapt to unforeseen frequency fluctuations and re
Externí odkaz:
https://doaj.org/article/c102548d75b4424495389bf5019ef5a6
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 12931-12944 (2024)
Deep neural networks (DNNs) have attained remarkable success in aerial detection tasks, yet they remain susceptible to adversarial samples, posing a significant challenge for their practical applications. While numerous transferable attacks have been
Externí odkaz:
https://doaj.org/article/1b67965cfb174ca1817c538ebd61b02b
Autor:
Hongqin Yang, Jiangbing Mao, Qinyong Ye, Magda Bucholc, Shuo Liu, Wenzhao Gao, Jie Pan, Jiawei Xin, Xuemei Ding
Publikováno v:
Frontiers in Aging Neuroscience, Vol 16 (2024)
IntroductionNovelty detection (ND, also known as one-class classification) is a machine learning technique used to identify patterns that are typical of the majority class and can discriminate deviations as novelties. In the context of Alzheimer's di
Externí odkaz:
https://doaj.org/article/bee5768d1eba49b080b7e2271317ac79
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 1, Pp 624-655 (2023)
A probabilistic neural network has been implemented to predict the malignancy of breast cancer cells, based on a data set, the features of which are used for the formulation and training of a model for a binary classification problem. The focus is pl
Externí odkaz:
https://doaj.org/article/cc330d0914cc49a39e604e7c426bae96
Akademický článek
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Akademický článek
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Publikováno v:
Entropy, Vol 25, Iss 11, p 1476 (2023)
The security of a network requires the correct identification and characterization of the attacks through its ports. This involves the follow-up of all the requests for access to the networks by all kinds of users. We consider the frequency of connec
Externí odkaz:
https://doaj.org/article/2ad77b9558084578aa7f5cdcea7a011f
Publikováno v:
Algorithms, Vol 16, Iss 9, p 438 (2023)
Visualization techniques for understanding and explaining machine learning models have gained significant attention. One such technique is the decision map, which creates a 2D depiction of the decision behavior of classifiers trained on high-dimensio
Externí odkaz:
https://doaj.org/article/ce62bd80665b47d79f40b6504f28b49d
Publikováno v:
IEEE Access, Vol 10, Pp 134356-134361 (2022)
We propose a method to form a non-uniform decision boundary (NUDB) for $M$ -ary quadrature amplitude modulation (MQAM) signals to reduce bit error floor (BEF) in the presence of phase error. We put our focus on angle distances between MQAM symbols an
Externí odkaz:
https://doaj.org/article/ff0631621a214287ae3603a8d71c0ee3
Publikováno v:
IEEE Access, Vol 10, Pp 114008-114015 (2022)
Researchers have continuously sought effective ways to detect unknown (zero-day) cyberattacks in real time. Most current methods rely on pattern-recognition to identify known threats when they appear. Recently, machine learning anomaly detection tool
Externí odkaz:
https://doaj.org/article/795080a09dc743cba34652e3ac2f78fd