Zhu, Z., Z. Wang, T. Li, X. Wang, H. Liu, A. E. Hassanien, and W. Yang,
"Multi-knowledge extraction algorithm using Group Search Optimization for brain dataset analysis",
Computing for Sustainable Global Development (INDIACom), 2015 2nd International Conference on: IEEE, pp. 1891–1896, 2015.
Abstractn/a
Zhang, S., F. Hu, S. - L. Jui, A. E. Hassanien, and K. Xiao,
"Unsupervised Brain MRI Tumor Segmentation with Deformation-Based Feature",
The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), November 28-30, 2015, Beni Suef, Egypt: Springer International Publishing, pp. 173–181, 2016.
Abstractn/a
Zhang, S., F. Hu, S. - L. Jui, A. E. Hassanien, and K. Xiao,
"Unsupervised Brain MRI Tumor Segmentation with Deformation-Based Feature",
the 1st International Conference on Advanced Intelligent Systems and Informatics (AISI’15) Springer, Beni Suef University, Beni Suef, Eg, Nov. 28-30, 2015.
Zawbaa, H. M., N. El-Bendary, A. E. Hassanien, and T. - H. Kim,
"Event detection based approach for soccer video summarization using machine learning",
Int J Multimed Ubiquitous Eng, vol. 7, no. 2, pp. 63–80, 2012.
Abstractn/a
Zawbaa, H. M., and A. E. Hassanien,
Automatic Soccer Video Summarization,
, Cairo, Cairo Unversity, 2012.
Abstract This thesis presents an automatic soccer video summarization system using machine learning (ML) techniques. The proposed system is composed of ve phases. Namely; in the pre-processing phase, the system segments the whole video stream into small video shots. Then, in the shot processing
phase, it applies two types of classi cation (shot type classi cation and play / break classification) to the video shots resulted from the pre-processing phase. Afterwards, in the replay detection phase, the proposed system applies two machine learning algorithms, namely; support vector machine (SVM) and arti cial neural network (ANN), for emphasizing important segments with championship logo appearance. Also, in the excitement event detection phase, the proposed system uses both machine learning algorithms for detecting the scoreboard which contain an information about the score of the game. The proposed system also uses k-means algorithm and Hough line transform for detecting vertical goal posts and Gabor lter for detecting goal net. Finally, in the event detection and summarization phase, the proposed system highlights the most important events during the match. Experiments on real soccer videos demonstrate encouraging results. The event detection and summarization has attained recall 94% and precision 97.3% for soccer match videos from ve international soccer championships.
Zawbaa, H. M., A. E. Hassanien, E. Emary, Waleed Yamany, and B. PARV,
"Hybrid flower pollination algorithm with rough sets for feature selection",
Computer Engineering Conference (ICENCO), 2015 11th International: IEEE, pp. 278–283, 2015.
Abstractn/a
Zawbaa, H. M., M. Abbass, M. Hazman, and A. E. Hassenian,
"Automatic Fruit Image Recognition System based on Shape and Color Features ",
The 2nd International Conference on Advanced Machine Learning Technologies and Applications , Egypt, November 17-19, , 2014.
Zawbaa, H. M., N. El-Bendary, A. E. Hassanien, and T. - H. Kim,
"Event detection based approach for soccer video summarization using machine learning",
Int J Multimed Ubiquitous Eng, vol. 7, no. 2, pp. 63–80, 2012.
Abstractn/a
]