10

Academic Experinece

6

Industrial Experience

6

Research Experience

Professional Affiliations

Pakistan Engineering Council
IEEE

Recent Publications

Articles
A Naeem, MS Farooq, A Khelifi, A Abid, “Malignant melanoma classification using deep learning: datasets, performance measurements, challenges and opportunities”, published in IEEE Access, Vol. 8, pp. 110575-110597, 2020.
M Tahir, A Naeem, H Malik, J Tanveer, RA Naqvi, SW Lee, “DSCC_Net: multi-classification deep learning models for diagnosing of skin cancer using dermoscopic images”, published in Cancers, Vol. 15(7), Article 2179, 2023.
A Naeem, T Anees, M Fiza, RA Naqvi, SW Lee, “SCDNet: a deep learning-based framework for the multiclassification of skin cancer using dermoscopy images”, published in Sensors, Vol. 22(15), Article 5652, 2022.
H Malik, T Anees, M Din, A Naeem, “CDC_Net: Multi-classification convolutional neural network model for detection of COVID-19, pneumothorax, pneumonia, lung Cancer, and tuberculosis using chest X-rays”, published in Multimedia Tools and Applications, Vol. 82(9), pp. 13855-13880, 2023.
A Naeem, T Anees, RA Naqvi, WK Loh, “A comprehensive analysis of recent deep and federated-learning-based methodologies for brain tumor diagnosis”, published in Journal of Personalized Medicine, Vol. 12(2), Article 275, 2022.
H Malik, A Naeem, RA Naqvi, WK Loh, “DMFL_Net: A federated learning-based framework for the classification of COVID-19 from multiple chest diseases using X-rays”, published in Sensors, Vol. 23(2), Article 743, 2023.
A Naeem, T Anees, M Khalil, K Zahra, RA Naqvi, SW Lee, “SNC_Net: skin cancer detection by integrating handcrafted and deep learning-based features using dermoscopy images”, published in Mathematics, Vol. 12(7), Article 1030, 2024.
A Naeem, T Anees, KT Ahmed, RA Naqvi, S Ahmad, T Whangbo, “Deep learned vectors’ formation using auto-correlation, scaling, and derivations with CNN for complex and huge image retrieval”, published in Complex & Intelligent Systems, Vol. 9(2), pp. 1729-1751, 2023.
A Naeem, T Anees, “DVFNet: A deep feature fusion-based model for the multiclassification of skin cancer utilizing dermoscopy images”, published in PLOS ONE, Vol. 19(3), Article e0297667, 2024.
S Riaz, A Naeem, H Malik, RA Naqvi, WK Loh, “Federated and transfer learning methods for the classification of Melanoma and Nonmelanoma skin cancers: a prospective study”, published in Sensors, Vol. 23(20), Article 8457, 2023.
H Malik, T Anees, A Naeem, RA Naqvi, WK Loh, “Blockchain-federated and deep-learning-based ensembling of capsule network with incremental extreme learning machines for classification of COVID-19 using CT scans”, published in Bioengineering, Vol. 10(2), Article 203, 2023.
H Malik, A Naeem, S Hassan, F Ali, RA Naqvi, DK Yon, “Multi-classification deep neural networks for identification of fish species using camera captured images”, published in PLOS ONE, Vol. 18(4), Article e0284992, 2023.
H Malik, A Naeem, A Sadeghi-Niaraki, RA Naqvi, SW Lee, “Multi-classification deep learning models for detection of ulcerative colitis, polyps, and dyed-lifted polyps using wireless capsule endoscopy images”, published in Complex & Intelligent Systems, Vol. 10(2), pp. 2477-2497, 2024.
A Naeem, AH Khan, S u din Ayubi, H Malik, “Predicting the metastasis ability of prostate cancer using machine learning classifiers”, published in Journal of Computing & Biomedical Informatics, Vol. 4(02), pp. 1-7, 2023.
M Khalil, A Naeem, RA Naqvi, K Zahra, SA Muqarib, SW Lee, “Deep learning-based classification of abrasion and ischemic diabetic foot sores using camera-captured images”, published in Mathematics, Vol. 11(17), Article 3793, 2023.
Abdul Mannan, Kashif Javed, Atta ur Rehman, Haroon A Babri, Serosh K Noon, “Cognition based Recognition of Partially Occluded Traffic Signs”, accepted at Scientia Iranica transactions on Computer Science & Engineering on 16-Jan-2022.
Noon, S. K., Amjad, M., Ali Qureshi, M., & Mannan, A. Computationally light deep learning framework to recognize cotton leaf diseases. Journal of Intelligent & Fuzzy Systems, (Preprint), 1-16.
Siddique, R., Raza, S., Mannan, A., Khalil, L., Alwaz, N., & Riaz, M. (2021). A modified NSGA approach for optimal sizing and allocation of distributed resources and battery energy storage system in distribution network. Materials Today: Proceedings, 47, S102-S109.
Noon, S. K., Amjad, M., Qureshi, M. A., & Mannan, A. (2020). Use of deep learning techniques for identification of plant leaf stresses: A review. Sustainable Computing: Informatics and Systems, 100443.
Mannan, A., Javed, K., & Noon, S. K. (2020, November). Statistical Boosting: A Preprocessing Technique to Enhance Performance of Machine Learning and Deep Learning Models on Partially Occluded Traffic Signs. In 2020 IEEE 23rd International Multitopic Conference (INMIC) (pp. 1-6). IEEE.
Mannan, A., Javed, K., Rehman, A. U., Babri, H. A., & Noon, S. K. (2019). Classification of degraded traffic signs using flexible mixture model and transfer learning. IEEE Access, 7, 148800-148813
Mannan, A., Javed, K., Noon, S. K., & Babri, H. A. (2019). Optimized segmentation and multiscale emphasized feature extraction for traffic sign detection and recognition. Journal of Intelligent & Fuzzy Systems, 36(1), 173-188.
Mannan, A., Javed, K., & Noon, S. K. (2017). Maximum Relevance Maximum Anti-Redundancy (mRmA) Feature Selection. Pakistan Journal of Engineering and Applied Sciences.
Noon, S. K., Javed, K., Mannan, A., & Babri, H. A. (2017). Recognizing traffic signs using flexible Discrete Cosine Transform (DCT) grid. Scientia Iranica, 24(3), 1384-1394.
Mannan, A., Babri, H. A., & Saeed, M. (2012). Offline shape recognition using flexible DCT grid. Scientia Iranica, 19(6), 1722-1730.