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| 1 | Robust image matching algorithm 显示文摘 | Abdul Ghafoorl Rao Naveed Iqhal Shoab Khan | 2003 | Video/image Processing and Multimedia Communications2003，，7： | 1 |
| 2 | Phytobezoar: a rare cause of late upper gastrointestinal perforation following gastric bypass surgery 显示文摘 | Sammut SJ Majid S Shoab S | 2012 | Ann R Coil Surg Engl2012，94，2： | 1 |
| 3 | Endothelial activation response to oral micronised flavonoid therapy in patients with chronic venous disease -a prospective study显示文摘 | Shoab SS Porter J Scurf JH | 1999 | Eur J Vasc Endovasc Surg1999，17，4： | 1 |
| 4 | Endothelial activation response to oral micronized flavonoid therapy in patients with chronic venous disease : A prospective study 显示文摘 | SHOAB S S PORTER J B SCURR J H | 1999 | Eur J Vasc Endovasc Surg1999，17，4： | 1 |
| 5 | Endothelial activation response to oral micronised flavonoid therapy in patients with chronic venous disease : a prospective study 显示文摘 | Shoab SS Porter J Scurr JH | 1999 | Eur J Vasc Endovasc Surg1999，17，4： | 1 |
| 6 | Endothelial activation response to oral micronised flavonoid therapy in patients with chronic venous disease-a prospective study显示文摘 | Shoab SS Porter J Scurr JH | | 0，，04： | 1 |
| 7 | Endothelial activation response to oral micronised flavonoid therapy in patients with chronic venous disease-a prospective study显示文摘 | Porter J Scurr JH | 1999 | Eur J Vasc Endovasc Surg1999，17，4： | 1 |
| 8 | Identification and classification of microaneurysms for early detection of diabetic retinopathy显示文摘 | M. Usman Akram Shehzad Khalid Shoab A. Khan | 2013 | Pattern Recognition2013，，1： | 1 |
| 9 | Endothelial activtion response to oralmicronised flavonoid therapy in patients with chronic venous disease,aprospectiva study显示文摘 | Shoab SS Poryer J Scurr JH | | 0，，： | 1 |
| 10 | Deep Q-Learning Based Optimal Query Routing Approach for Unstructured P2P Network显示文摘Deep Reinforcement Learning(DRL)is a class of Machine Learning(ML)that combines Deep Learning with Reinforcement Learning and provides a framework by which a system can learn from its previous actions in an environment to select its efforts in the future efficiently.DRL has been used in many application fields,including games,robots,networks,etc.for creating autonomous systems that improve themselves with experience.It is well acknowledged that DRL is well suited to solve optimization problems in distributed systems in general and network routing especially.Therefore,a novel query routing approach called Deep Reinforcement Learning based Route Selection(DRLRS)is proposed for unstructured P2P networks based on a Deep Q-Learning algorithm.The main objective of this approach is to achieve better retrieval effectiveness with reduced searching cost by less number of connected peers,exchangedmessages,and reduced time.The simulation results shows a significantly improve searching a resource with compression to k-Random Walker and Directed BFS.Here,retrieval effectiveness,search cost in terms of connected peers,and average overhead are 1.28,106,149,respectively. | Mohammad Shoab Abdullah Shawan Alotaibi | 2022 | Computers, Materials & Continua2022，，3： | 0 |
| 11 | Classification of Diabetic Macular Edema and Its Stages Using Color Fundus Image显示文摘Diabetic macular edema(DME)is a retinal thickening involving the center of the macula.It is one of the serious eye diseases which affects the central vision and can lead to partial or even complete visual loss.The only cure is timely diagnosis,prevention,and treatment of the disease.This paper presents an automated system for the diagnosis and classification of DME using color fundus image.In the proposed technique,first the optic disc is removed by applying some preprocessing steps.The preprocessed image is then passed through a classifier for segmentation of the image to detect exudates.The classifier uses dynamic thresholding technique by using some input parameters of the image.The stage classification is done on the basis of an early treatment diabetic retinopathy study(ETDRS)given criteria to assess the severity of disease.The proposed technique gives a sensitivity,specificity,and accuracy of 98.27%,96.58%,and 96.54%,respectively on publically available database. | Muhammad Zubair Shoab A.Khan Ubaid Ullah Yasin | 2014 | Journal of Electronic Science and Technology2014，12，2： | 0 |
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