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Khaled Younis
Khaled Younis
CEO and Founder, MedAiConsult
Correu electrònic verificat a ge.com
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Arabic Hand-Written Character Recognition Based on Deep Convolutional Neural Networks
K Younis
Jordanian Journal of Computers and Information Technology 3 (3), 186-200, 2017
1242017
Docking-based comparative intermolecular contacts analysis as new 3-D QSAR concept for validating docking studies and in silico screening: NMT and GP inhibitors as case studies
MO Taha, M Habash, Z Al-Hadidi, A Al-Bakri, K Younis, S Sisan
Journal of chemical information and modeling 51 (3), 647-669, 2011
862011
Discovery of new MurF inhibitors via pharmacophore modeling and QSAR analysis followed by in-silico screening
MO Taha, N Atallah, AG Al-Bakri, C Paradis-Bleau, H Zalloum, KS Younis, ...
Bioorganic & medicinal chemistry 16 (3), 1218-1235, 2008
762008
Handwritten Arabic character recognition using multiple classifiers based on letter form
GA Abandah, KS Younis, MZ Khedher
Proceedings of the 5th International Conference on Signal Processing …, 2008
752008
A new implementation of deep neural networks for optical character recognition and face recognition
KS Younis, AA Alkhateeb
Proceedings of the new trends in information technology, 157-162, 2017
342017
Real-time epileptic seizure detection during sleep using passive infrared sensors
O Hanosh, R Ansari, K Younis, AE Cetin
IEEE Sensors Journal 19 (15), 6467-6476, 2019
272019
Cluster merging based on weighted mahalanobis distance with application in digital mammograph
K Younis, M Karim, R Hardie, J Loomis, S Rogers, M DeSimio
Proceedings of the IEEE 1998 National Aerospace and Electronics Conference …, 1998
271998
Weighted Mahalanobis distance for hyper-ellipsoidal clustering
KS Younis
221996
Continuous Signals and Systems with MATLAB®
TS ElAli
CRC press, 2020
192020
Docking-based comparative intermolecular contacts analysis and in silico screening reveal new potent acetylcholinesterase inhibitors
M Habash, S Abuhamdah, K Younis, MO Taha
Medicinal Chemistry Research 26 (11), 2768-2784, 2017
152017
Reproducibility of deep learning algorithms developed for medical imaging analysis: A systematic review
M Moassefi, P Rouzrokh, GM Conte, S Vahdati, T Fu, A Tahmasebi, ...
Journal of Digital Imaging 36 (5), 2306-2312, 2023
92023
Embedded system implementation for material recognition using deep learning
KS Younis, W Ayyad, A Al-Ajlony
2017 IEEE Jordan Conference on Applied Electrical Engineering and Computing …, 2017
92017
Optimization of extended-release hydrophilic matrix tablets by support vector regression
N Al-Zoubi, K Kachrimanis, K Younis, S Malamataris
Drug development and industrial pharmacy 37 (1), 80-87, 2011
92011
Vector quantization based on dynamic adjustment of Mahalanobis distance
KS Younis, SK Rogers, MP DeSimio
Proceedings of the IEEE 1996 National Aerospace and Electronics Conference …, 1996
81996
Current state of community-driven radiological ai deployment in medical imaging
V Gupta, B Erdal, C Ramirez, R Floca, B Genereaux, S Bryson, C Bridge, ...
JMIR AI 3 (1), e55833, 2024
62024
Checklist for Reproducibility of Deep Learning in Medical Imaging
M Moassefi, Y Singh, GM Conte, B Khosravi, P Rouzrokh, S Vahdati, ...
Journal of Imaging Informatics in Medicine, 1-10, 2024
62024
A new algorithm for detecting the optimal number of substructures in the data
KS Younis, MP DeSimio, SK Rogers
Proceedings of the IEEE 1997 National Aerospace and Electronics Conference …, 1997
41997
Leveraging deep learning for orientation detection and correction of X-ray images
K Younis, P Dalal, G Vera, K Nye, G Rao
Society for Imaging Informatics in Medicine (SIIM), Conference on Machine …, 2020
32020
Evaluating and selecting features for recognizing handwritten Arabic characters
G Abandah, M Khedher, K Younis
Tech. Report, Computer Eng. Dept., The Univ. of Jordan, 2007
32007
Persistence Image from 3D Medical Image: Superpixel and Optimized Gaussian Coefficient
Y Zhu, Y Singh, K Younis, S Bao, Y Huo
arXiv preprint arXiv:2408.07905, 2024
12024
En aquests moments el sistema no pot dur a terme l'operació. Torneu-ho a provar més tard.
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