Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Mohammed Eshtay"'
Publikováno v:
Egyptian Informatics Journal, Vol 24, Iss 3, Pp 100386- (2023)
Predicting defect-prone software components can play a significant role in allocating relevant testing resources to fault-prone modules and hence increasing the business value of software projects. Most of the current software defect prediction studi
Externí odkaz:
https://doaj.org/article/a7d5d828b963401881cdce53a39b3c80
Autor:
Mohammad Alauthman, Ahmad Al-qerem, Bilal Sowan, Ayoub Alsarhan, Mohammed Eshtay, Amjad Aldweesh, Nauman Aslam
Publikováno v:
Informatics, Vol 10, Iss 1, p 28 (2023)
Developing an effective classification model in the medical field is challenging due to limited datasets. To address this issue, this study proposes using a generative adversarial network (GAN) as a data-augmentation technique. The research aims to e
Externí odkaz:
https://doaj.org/article/3850ca5d28894d5a91a73c4fb9a06d9c
Publikováno v:
Applied Sciences, Vol 10, Iss 11, p 3706 (2020)
Nowadays, smartphones are an essential part of people’s lives and a sign of a contemporary world. Even that smartphones bring numerous facilities, but they form a wide gate into personal and financial information. In recent years, a substantial inc
Externí odkaz:
https://doaj.org/article/562edd287fe94e0282da3341df58be83
Autor:
Hamad Alsawalqah, Neveen Hijazi, Mohammed Eshtay, Hossam Faris, Ahmed Al Radaideh, Ibrahim Aljarah, Yazan Alshamaileh
Publikováno v:
Applied Sciences, Vol 10, Iss 5, p 1745 (2020)
Software defect prediction is a promising approach aiming to improve software quality and testing efficiency by providing timely identification of defect-prone software modules before the actual testing process begins. These prediction results help s
Externí odkaz:
https://doaj.org/article/89800d73c1664eaa82da8de048a596e3
Publikováno v:
Neural Computing and Applications. 35:5291-5317
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::23337feff1a6bac2b8505fffca804c48
https://doi.org/10.1007/s00521-022-07950-7
https://doi.org/10.1007/s00521-022-07950-7
Publikováno v:
Neural Computing and Applications. 33:5507-5524
Random Weight Networks have been extensively used in many applications in the last decade because it has many strong features such as fast learning and good generalization performance. Most of the traditional training techniques for Random Weight Net
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::929ceb12c802ea3227dd3bd1fcb48ef9
https://doi.org/10.1007/s00521-020-05329-0
https://doi.org/10.1007/s00521-020-05329-0
Publikováno v:
International Journal of Machine Learning and Cybernetics. 11:1801-1823
Extreme Learning Machine (ELM) is a learning algorithm proposed recently to train single hidden layer feed forward networks (SLFN). It has many attractive properties that include better generalization performance and very fast learning. ELM starts by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7440e1aec51833921b087bf5b2597d0f
https://doi.org/10.1007/s13042-020-01073-y
https://doi.org/10.1007/s13042-020-01073-y
Publikováno v:
Proceedings of the 18th International Conference on Web Information Systems and Technologies.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::358cacca733b08a69098acd228a0ed15
https://doi.org/10.5220/0011589200003318
https://doi.org/10.5220/0011589200003318
Publikováno v:
Scopus-Elsevier
NoSQL database systems have emerged and developed at an accelerating rate in the last years. Attractive properties such as scalability and performance, which are needed by many applications today, contributed to their increasing popularity. Time is v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::127a8564ac74d0a3b3543f099a5d1ce3
https://doi.org/10.47839/ijc.18.1.1272
https://doi.org/10.47839/ijc.18.1.1272
Publikováno v:
ACIT
A class decomposition is one of the possible solutions and the most important factors of success for the improvement of classification performance. The idea is to transform a dataset by categorizing each class label into groups or clusters. Thus, the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::712e6b7f9aae82be79a15b4f6ed6015e
https://doi.org/10.1109/acit50332.2020.9300084
https://doi.org/10.1109/acit50332.2020.9300084