Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Fahad Sohrab"'
Publikováno v:
IEEE Access, Vol 12, Pp 81017-81029 (2024)
Detecting malware is crucial for ensuring the security of computer systems. Traditional machine learning models face challenges in effectively detecting malware, mainly due to the class imbalance problem, where the number of malware samples is signif
Externí odkaz:
https://doaj.org/article/7a8363afe3fb443bafb463c78f4dcc96
Publikováno v:
IEEE Access, Vol 8, Pp 122013-122025 (2020)
In this paper, we propose a novel method for transforming data into a low-dimensional space optimized for one-class classification. The proposed method iteratively transforms data into a new subspace optimized for ellipsoidal encapsulation of target
Externí odkaz:
https://doaj.org/article/3a28fb3e79cf4475a8d591d305f57639
Publikováno v:
Sohrab, F, Iosifidis, A, Gabbouj, M & Raitoharju, J 2023, ' Graph-embedded subspace support vector data description ', Pattern Recognition, vol. 133, 108999 . https://doi.org/10.1016/j.patcog.2022.108999
In this paper, we propose a novel subspace learning framework for one-class classification. The proposed framework presents the problem in the form of graph embedding. It includes the previously proposed subspace one-class techniques as its special c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::104c77be6f226cfa41d27945700a0ace
https://doi.org/10.1016/j.patcog.2022.108999
https://doi.org/10.1016/j.patcog.2022.108999
An image anomaly localization method based on the successive subspace learning (SSL) framework, called AnomalyHop, is proposed in this work. AnomalyHop consists of three modules: 1) feature extraction via successive subspace learning (SSL), 2) normal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6c6c91a3859753c0d29ac780fafd0709
http://arxiv.org/abs/2105.03797
http://arxiv.org/abs/2105.03797
Publikováno v:
UbiComp/ISWC Adjunct
In this work, we examine the suitability of automatic facial expression recognition to be used for satisfaction analysis in an Empathic Building environment. We use machine learning based facial expression recognition on the working stations to integ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c42052abc64c5633c1e826d973be1f3c
https://trepo.tuni.fi/handle/10024/130121
https://trepo.tuni.fi/handle/10024/130121
Autor:
Jenni Raitoharju, Fahad Sohrab
Publikováno v:
SSCI
Insect monitoring is crucial for understanding the consequences of rapid ecological changes, but taxa identification currently requires tedious manual expert work and cannot be scaled-up efficiently. Deep convolutional neural networks (CNNs), provide
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::01a6ece72bc947e839ee44ae25fe464e
http://arxiv.org/abs/2002.10420
http://arxiv.org/abs/2002.10420
Publikováno v:
Sohrab, F, Raitoharju, J, Iosifidis, A & Gabbouj, M 2020, ' Ellipsoidal Subspace Support Vector Data Description ', IEEE Access, vol. 8, 9133428, pp. 122013-122025 . https://doi.org/10.1109/ACCESS.2020.3007123
IEEE Access, Vol 8, Pp 122013-122025 (2020)
IEEE Access, Vol 8, Pp 122013-122025 (2020)
In this paper, we propose a novel method for transforming data into a low-dimensional space optimized for one-class classification. The proposed method iteratively transforms data into a new subspace optimized for ellipsoidal encapsulation of target
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::216cbf8feaa9e5e7bb2b8b7bead9376c
https://trepo.tuni.fi/handle/10024/127452
https://trepo.tuni.fi/handle/10024/127452
Publikováno v:
Sohrab, F, Raitoharju, J, Gabbouj, M & Iosifidis, A 2018, Subspace Support Vector Data Description . in Proceedings of the 24th International Conference on Pattern Recognition : ICPR 2018 . vol. 2018, IEEE, International Conference on Pattern Recognition, vol. 2018, pp. 722-727, International Conference on Pattern Recognition 2018, Beijing, China, 20/08/2018 . https://doi.org/10.1109/ICPR.2018.8545819
ICPR
ICPR
This paper proposes a novel method for solving one-class classification problems. The proposed approach, namely Subspace Support Vector Data Description, maps the data to a subspace that is optimized for one-class classification. In that feature spac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3dc0b6b79339463f6c60cf39f25f9611
https://pure.au.dk/portal/da/publications/subspace-support-vector-data-description(890ecba0-2fa9-4c96-ae52-c69692c0a427).html
https://pure.au.dk/portal/da/publications/subspace-support-vector-data-description(890ecba0-2fa9-4c96-ae52-c69692c0a427).html
Autor:
Fahad Sohrab, Hakan Erdogan
Publikováno v:
EUSIPCO
This paper proposes a novel approach for denoising single-channel noisy speech signals. A speech dictionary and multiple noise dictionaries are trained using nonnegative matrix factorization (NMF). After observing the mixed signal, first the type of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::068fb458547b895bcd62c43b21996cd2
Autor:
Fahad Sohrab
Publikováno v:
Tampere University
Machine learning deals with discovering the knowledge that governs the learning process. The science of machine learning helps create techniques that enhance the capabilities of a system through the use of data. Typical machine learning techniques id
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::21597520f436d52f6bd060daa30587d0
https://researchportal.tuni.fi/en/publications/e6f90e1f-29c5-4e30-bcde-e63062d0045c
https://researchportal.tuni.fi/en/publications/e6f90e1f-29c5-4e30-bcde-e63062d0045c