Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Maedeh Beheshti"'
Publikováno v:
IEEE Access, Vol 12, Pp 66478-66494 (2024)
Deep learning models are widely used in healthcare systems. However, deep learning models are vulnerable to attacks themselves. Significantly, due to the black-box nature of the deep learning model, it is challenging to detect attacks. Furthermore, d
Externí odkaz:
https://doaj.org/article/c2682918c3b54cb0a3d003fb11d6b3fc
Publikováno v:
Türk Nöroloji Dergisi, Vol 22, Iss 4, Pp 156-160 (2016)
Objective: Some patients with migraine headache still experience severe migraine attacks despite use of proper prophylactic treatments. There are several treatments for refractory migraine (RM), one of which is abobotulinum toxin A (Dysport). This st
Externí odkaz:
https://doaj.org/article/b2d125276fd645b18fad4281d0c185f5
Autor:
Zahra Jadidi, Shantanu Pal, Nithesh Nayak K, Arawinkumaar Selvakkumar, Chih-Chia Chang, Maedeh Beheshti, Alireza Jolfaei
Publikováno v:
2022 International Conference on Computer Communications and Networks (ICCCN).
In this study, we focus on the impact of adversarial attacks on deep learning-based anomaly detection in CPS networks and implement a mitigation approach against the attack by retraining models using adversarial samples. We use the Bot-IoT and Modbus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35ff4935225b2efc2cbdc5506e5e8c4a
https://doi.org/10.1109/icccn54977.2022.9868845
https://doi.org/10.1109/icccn54977.2022.9868845
Publikováno v:
JAMIA open. 5(2)
ObjectiveTo summarize applications of natural language processing (NLP) in model informed drug development (MIDD) and identify potential areas of improvement.Materials and MethodsPublications found on PubMed and Google Scholar, websites and GitHub re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f7e4deaf17f560078f4bd67107a7d93
https://pubmed.ncbi.nlm.nih.gov/35702625
https://pubmed.ncbi.nlm.nih.gov/35702625
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 34:2563-2578
Accurate segmentation of fluorescence images has become increasingly important for recognizing cell nucleus that have the phenotype of interest in biomedical applications. In this study an ensemble based method is proposed for the segmentation of cel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::134ae00d7b9607f0775c7c09c9793eaf
https://doi.org/10.3233/jifs-17466
https://doi.org/10.3233/jifs-17466
Autor:
Mehran Homam, Maedeh Beheshti Saadat, Mostafa Khorashadizadeh, Morteza Mazloum Farsi Baf, Afrouz Alipour
Publikováno v:
Türk Nöroloji Dergisi, Vol 22, Iss 4, Pp 156-160 (2016)
Objective: Some patients with migraine headache still experience severe migraine attacks despite use of proper prophylactic treatments. There are several treatments for refractory migraine (RM), one of which is abobotulinum toxin A (Dysport). This st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b83efc11980cfa1cf1e20d0b546d3db4
https://doi.org/10.4274/tnd.15986
https://doi.org/10.4274/tnd.15986
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 24:333-346
Content-based image retrieval CBIR, as a well-known retrieval method, has been widely used in various applications. The basis of this method is on features like color, texture and shape. Color image histograms are very useful tools for this purpose.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::50a605e5d126b46f52e161e4538a52c2
https://doi.org/10.3233/ifs-2012-0557
https://doi.org/10.3233/ifs-2012-0557
Publikováno v:
DICTA
The accurate segmentation of biomedical images has become increasingly important for recognizing cells that have the phenotype of interest in biomedical applications. In order to improve the conventional deterministic segmentation models, this paper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3754db855b8fb9acede2da5cbec52e99
https://doi.org/10.1109/dicta.2015.7371241
https://doi.org/10.1109/dicta.2015.7371241
Image Segmentation Based on Graph-Cut Models and Probabilistic Graphical Models: A Comparative Study
Autor:
Maedeh Beheshti, Alan Wee-Chung Liew
Publikováno v:
Communications in Computer and Information Science ISBN: 9783662456514
ICMLC (CCIS volume)
ICMLC (CCIS volume)
Image segmentation has been one of the most important unsolved problems in computer vision for many years. Recently, there have been great effort in producing better segmentation algorithms. The purpose of this paper is to introduce two proposed grap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5e5992ec75aef407af12b27fb66c0e5
https://doi.org/10.1007/978-3-662-45652-1_37
https://doi.org/10.1007/978-3-662-45652-1_37
