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Syed Muhammad Naqi
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2020 – today
- 2023
- [j6]Sahar Gull, Shahzad Akbar, Syed Muhammad Naqi:
A deep learning approach for multi-stage classification of brain tumor through magnetic resonance images. Int. J. Imaging Syst. Technol. 33(5): 1745-1766 (2023) - [j5]Divya Ramachandran, Syed Muhammad Naqi, Ganeshkumar Perumal, Qaisar Abbas:
DLTN-LOSP: A Novel Deep-Linear-Transition-Network-Based Resource Allocation Model with the Logic Overhead Security Protocol for Cloud Systems. Sensors 23(20): 8448 (2023) - [j4]Ganeshkumar Perumal, Gopalakrishnan Subburayalu, Qaisar Abbas, Syed Muhammad Naqi, Imran Qureshi:
VBQ-Net: A Novel Vectorization-Based Boost Quantized Network Model for Maximizing the Security Level of IoT System to Prevent Intrusions. Syst. 11(8): 436 (2023) - [c2]Zahra Abbas, Mario Fiorino, Syed Muhammad Naqi, Musarat Abbas:
COVID-19 Prediction Infrastructure Using Deep Learning. Intelligent Environments (Workshops) 2023: 125-134 - 2020
- [j3]Syed Muhammad Naqi, Muhammad Sharif, M. Arfan Jaffar:
Lung nodule detection and classification based on geometric fit in parametric form and deep learning. Neural Comput. Appl. 32(9): 4629-4647 (2020)
2010 – 2019
- 2019
- [j2]Syed Muhammad Naqi, Muhammad Sharif, Muhammad Ikram Ullah Lali:
A 3D nodule candidate detection method supported by hybrid features to reduce false positives in lung nodule detection. Multim. Tools Appl. 78(18): 26287-26311 (2019) - 2018
- [j1]Syed Muhammad Naqi, Muhammad Sharif, Mussarat Yasmin:
Multistage segmentation model and SVM-ensemble for precise lung nodule detection. Int. J. Comput. Assist. Radiol. Surg. 13(7): 1083-1095 (2018) - 2010
- [c1]Qurat-ul Ain, Irfan Mehmood, Syed Muhammad Naqi, M. Arfan Jaffar:
Bayesian Classification Using DCT Features for Brain Tumor Detection. KES (1) 2010: 340-349
Coauthor Index
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