Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Haifa F. Alhasson"'
Autor:
Ashifur Rahman, Md. Mohsin Kabir, M. F. Mridha, Mohammed Alatiyyah, Haifa F. Alhasson, Shuaa S. Alharbi
Publikováno v:
IEEE Access, Vol 12, Pp 39689-39716 (2024)
Speech recognition is a captivating process that revolutionizes human-computer interactions, allowing us to interact and control machines through spoken commands. The foundation of speech recognition lies in understanding a given language’s linguis
Externí odkaz:
https://doaj.org/article/a57667eb41e645bc8e1f096e93a16c79
Publikováno v:
Diagnostics, Vol 14, Iss 13, p 1402 (2024)
Breast cancer diagnosis from histopathology images is often time consuming and prone to human error, impacting treatment and prognosis. Deep learning diagnostic methods offer the potential for improved accuracy and efficiency in breast cancer detecti
Externí odkaz:
https://doaj.org/article/1a67601b47f54fddaae525cd166005e4
Autor:
Haifa F. Alhasson, Elaf Almozainy, Manar Alharbi, Naseem Almansour, Shuaa S. Alharbi, Rehan Ullah Khan
Publikováno v:
Applied Sciences, Vol 13, Iss 23, p 12589 (2023)
The recent outbreak of monkeypox has raised significant concerns in the field of public health, primarily because it has quickly spread to over 40 countries outside of Africa. Detecting monkeypox in its early stages can be quite challenging because i
Externí odkaz:
https://doaj.org/article/ccc29473455e492a966c5f997248c560
Publikováno v:
Applied Sciences, Vol 13, Iss 23, p 12771 (2023)
Dental caries is one of the most prevalent and chronic diseases worldwide. Dental X-ray radiography is considered a standard tool and a valuable resource for radiologists to identify dental diseases and problems that are hard to recognize by visual i
Externí odkaz:
https://doaj.org/article/a8412d946f8645f78844dc0190b714fb
Publikováno v:
The visual computer, 2021, Vol.37(8), pp.2263-2283 [Peer Reviewed Journal]
Curvilinear structure detection and quantification is a large research area with many imaging applications in fields such as biology, medicine, and engineering. Curvilinear enhancement is often used as a pre-processing stage for ridge detection, but
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b1271674baf57965929bedd47b1309c
http://dro.dur.ac.uk/31670/
http://dro.dur.ac.uk/31670/
Publikováno v:
Signal, image and video processing, 2019, Vol.13(5), pp.941-949 [Peer Reviewed Journal]
In this paper, a new approach is proposed to extract an ordered sequence of curvilinear structures in images, capturing the largest and most influential paths first and then progressively extracting smaller paths until a prespecified size is reached.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::288acbc0df544791e38233a8abb1f5ec
https://doi.org/10.1007/s11760-019-01431-6
https://doi.org/10.1007/s11760-019-01431-6
Publikováno v:
Methods, 2020, Vol.173, pp.3-15 [Peer Reviewed Journal]
Quantification and modelling of curvilinear structures in 2D and 3D images is a common challenge in a wide range of biomedical applications. Image enhancement is a crucial pre-processing step for curvilinear structure quantification. Many of the exis
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030110239
ECCV Workshops (6)
ECCV Workshops (6)
The detection of vascular structures from noisy images is a fundamental process for extracting meaningful information in many applications. Most well-known vascular enhancing techniques often rely on Hessian-based filters. This paper investigates the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::02ebd327303665caba273e7bd5027677
https://doi.org/10.1007/978-3-030-11024-6_26
https://doi.org/10.1007/978-3-030-11024-6_26
Autor:
Boguslaw Obara, Haifa F. Alhasson
Publikováno v:
BIBE
(2016). 2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) : 31 October–2 November 2016 Taichung, Taiwan ; proceedings. Piscataway, NJ: IEEE, pp. 230-237
(2016). 2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE) : 31 October–2 November 2016 Taichung, Taiwan ; proceedings. Piscataway, NJ: IEEE, pp. 230-237
The accurate analysis of biological networks, enabled by the precise capture of their individual components, can reveal important underlying biological principles. Efficient image processing techniques are required to precisely identify and quantify