S
Syed Muhammad Saqlain
Researcher at International Islamic University, Islamabad
Publications - 14
Citations - 243
Syed Muhammad Saqlain is an academic researcher from International Islamic University, Islamabad. The author has contributed to research in topics: Incremental decision tree & Computer science. The author has an hindex of 6, co-authored 13 publications receiving 170 citations.
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Journal ArticleDOI
Fisher score and Matthews correlation coefficient-based feature subset selection for heart disease diagnosis using support vector machines
Syed Muhammad Saqlain,Muhammad Sher,Faiz Ali Shah,Imran Khan,Muhammad Usman Ashraf,Muhammad Usman Ashraf,Muhammad Awais,Anwar Ghani +7 more
TL;DR: A clinical heart disease diagnostic system is presented by proposing feature subset selection methodology with an object of achieving improved performance and the proposed methodology is validated through accuracy, specificity and sensitivity using four UCI datasets.
Journal ArticleDOI
Ontology Based Semantic Search in Holy Quran
TL;DR: It is proposed that the concepts of ontology of semantic web can be applied for carrying out semantic search in Holy Quran and certain recommendation for the project of attaining semantic search from all domains and resultantly all text of Holy Quran is proposed.
Journal ArticleDOI
An efficient cryptographic technique using modified Diffie–Hellman in wireless sensor networks:
Shahwar Ali,A Humaria,M Sher Ramzan,Imran Khan,Syed Muhammad Saqlain,Anwar Ghani,J Zakia,Bander A. Alzahrani +7 more
TL;DR: A data security approach with less computational and response times based on a modified version of Diffie–Hellman, modified to secure it against attacks by generating a hash of each value that is transmitted over the network.
Proceedings ArticleDOI
A robust and enhanced approach for human detection in crowd
TL;DR: Comparison results of the methodology with existing techniques are presented and the results clearly proved that the proposed technique outperforms the existing techniques and this is proved by producing comparative results.
Journal ArticleDOI
Fingerprint image classification using local diagonal and directional extrema patterns
TL;DR: The proposed LDDEP descriptor is compared with the existing methods on two databases, namely National Institute of Standards Technology Special Database 4 (NIST SD 4) and Fingerprint Verification Competition (FVC), and gave higher accuracies compared to theexisting methods.