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Abdul Waheed
Researcher at Hazara University
Publications - 42
Citations - 409
Abdul Waheed is an academic researcher from Hazara University. The author has contributed to research in topics: Signcryption & Encryption. The author has an hindex of 7, co-authored 40 publications receiving 186 citations. Previous affiliations of Abdul Waheed include Seoul National University.
Papers
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Journal ArticleDOI
A Trust-Based Energy-Efficient and Reliable Communication Scheme (Trust-Based ERCS) for Remote Patient Monitoring in Wireless Body Area Networks
TL;DR: A trust-based communication scheme to ensure the reliability and privacy of WBAN is proposed and a cooperative communication approach is used, while for privacy preservation, a cryptography mechanism is used to ensure reliability.
Journal Article
Hepatocellular carcinoma (HCC) and diagnostic significance of A-fetoprotein (AFP).
Jawed Altaf Baig,Junaid Mahmood Alam,Syed Riaz Mahmood,Muhammad Aslam Baig,Rabia Shaheen,Ishrat Sultana,Abdul Waheed +6 more
TL;DR: It is concluded that AFP is a significant markers for Hepatocellular carcinoma, helpful in assessing problems in management of HCC and monitoring treatment regiments.
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Efficient and secure attribute-based heterogeneous online/offline signcryption for body sensor networks based on blockchain:
TL;DR: An efficient and secure heterogeneous scheme for body sensor networks is proposed, in which biosensor nodes use a certificate-less cryptography environment to resolve the key escrow and certificate-management problems, while MS uses a public key infrastructure environment to enhance the scalability of the networks.
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Unsupervised color image segmentation: A case of RGB histogram based K-means clustering initialization.
Sadia Basar,Mushtaq Ali,Gilberto Ochoa-Ruiz,Mahdi Zareei,Abdul Waheed,Abdul Waheed,Awais Adnan +6 more
TL;DR: A novel and adaptive initialization approach to determine the number of clusters and find the initial central points of clusters for the standard K-means algorithm to solve the segmentation problem of color images and shows that the proposed technique outperforms the other existing clustering techniques by optimizing the segmentsation quality and possibly reducing the classification error.
Journal ArticleDOI
Acute Myeloid Leukemia (AML) Detection Using AlexNet Model
Maneela Shaheen,Rafiullah Khan,R. R. Biswal,Mohib Ullah,Atif Khan,M. Irfan Uddin,Mahdi Zareei,Abdul Waheed,Abdul Waheed +8 more
TL;DR: In this article, an AlexNet-based classification model was proposed to detect Acute Myeloid Leukemia (AML) in microscopic blood images and compared its performance with LeNet-5-based model in Precision, Recall, Accuracy, and Quadratic Loss.