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Muhammad Ahmad

Muhammad Ahmad

Assistant Professor
  • Department of Computer Science
  • dr.ahmad@nu.edu.pk
  • (041) 111-128-128
  • Ext: 159

Introduction

Muhammad Ahmad

Muhammad Ahmad is currently working as an Assistant Professor at the National University of Computer & Emerging Sciences (FAST-NUCES). Prior to that, he was been affiliated with Khwaja Fareed University of Engineering and Information Technology, as an Assistant Professor. He has also served as a Lecturer/Instructor, Research Fellow, Research Associate, and Research Assistant for a number of national and international universities. He is the author of over 70 peer-reviewed articles. He is supervising/co-supervising (supervised) several graduates (MS and Ph.D.). His research interest includes Hyperspectral Imaging, Remote Sensing, Machine Learning, Computer Vision, and Wearable Computing.

Education

  • Doctor of Philosophy (Hyperspectral Imaging)
  • Innopolis University, Innopolis, Russia.
  • Masters of Science (Hyperspectral Imaging)
  • International Islamic University, Islamabad, Pakistan
  • Bachelor of Science
  • (Metric Spaces / Mathematical Reasoning for Machine Learning Models), GC
    University, Pakistan

Publications

HEC Recognized Impact factor publications

1. M. Ahmad, U. Ghous, D. Hong, A. M. Khan, J. Yao, S. Wang, and J. Chanussot, “ A Disjoint Samples-based 3D-CNN with Active Transfer Learning for Hyperspectral Image Classification”, IEEE Transactions on Geoscience and Remote Sensing, (early access), (IF. 8.125), 2022.

2. S.K.Roy, et.al., “Hyperspectral and LiDAR Data Classification Using Joint CNNs and Morphological Feature Learning” IEEE Transactions on Geoscience and Remote Sensing, (early access) (IF. 8.125), 2022.

3. M. Ahmad, et.al., “Hybrid Dense Network with Attention Mechanism for Hyperspectral Image Classification”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, (IF. 4.715), 2022.

4. M. Ahmad, et.al., “Hyperspectral Image Classification – Traditional to Deep Models: A Survey for Future Prospects”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 968-999, (IF. 4.715), 2022.

5. M. Ahmad, et.al., “A Fast and Compact 3-D CNN for Hyperspectral Image Classification”, IEEE Geoscience and Remote Sensing Letters, (IF. 5.343), pp. 1-5, 2021.

6. M. Ahmad, et.al., “Regularized CNN Feature Hierarchy for Hyperspectral Image Classification”, Remote Sensing, vol. 13(12), pp. 2275, (IF. 5.349), 2021.

7. M. Ahmad, et.al., “Artifacts of Different Dimension Reduction Methods on Hybrid CNN Feature Hierarchy for Hyperspectral Image Classification”, Optik, vol. 246, (IF. 2.84), 2021.

8. H. Ayaz, et.al., “Classification of Apple Disease Based on Non-Linear Deep Features”, Applied Sciences, vol. 11(14), pp. 6422, (IF. 2.838), 2021.

9. M. H. Khan, et.al., “Hyperspectral imaging-based unsupervised adulterated red chili content transformation for classification: Identification of red chili adulterants”, Neural Computing and Applications (NCAA), (IF. 5.606), 2021.

10. M. Zulfiqar, et.al., “Hyperspectral Imaging for Bloodstain Identification”, Sensors, (IF. 3.576), vol. 21(9), 2021.

11. M. Ahmad, “Ground Truth Labeling and Samples Selection for Hyperspectral Image Classification”, Optik, (IF. 2.84), vol. 230, 2021.

12. H. Ayaz, et.al., “Hyperspectral Imaging for Minced Meat Classification Using Nonlinear Deep Features”, vol. 10(21), pp. 7783, Applied Sciences, (IF. 2.679), 2020.

13. Z. Saleem, M. Ahmad, et.al., “Prediction of Microbial Spoilage and Shelf-Life of Bakery Products through Hyperspectral Imaging”, IEEE Access, vol. 8, pp. 176986-176996, (IF. 4.098), 2020.

14. H. Ayaz, et.al., “Myoglobin-based Classification of Minced meat using Hyperspectral Imaging”, Applied Sciences, (IF. 2.679), 10, 6862, 2020.

15. M. H. Khan, et.al., “Hyperspectral Imaging for Color Adulteration Detection in Red Chili”, Applied Sciences, (IF. 2.679), vol. 10, pp. 5955, 2020.

16. M. Ahmad, et.al., “Multiclass Non-Randomized Spectral-Spatial Active Learning for Hyperspectral Image Classification”, Applied Sciences, (IF. 2.679), 2020.
17. M. Ahmad, et.al., “Spatial-prior Generalized Fuzziness Extreme Learning Machine Autoencoder-based Active Learning for Hyperspectral Image Classification”, Optik, vol. 206, (IF. 2.84), 2020.

18. M. Ahmad, et.al., “Spatial Prior Fuzziness Pool-based Interactive Classification of Hyperspectral Images”, Remote Sensing, vol. 11(5), (IF. 5.349), 2019.

19. M. Ahmad, et.al., “Segmented and Non-Segmented Stacked Denoising Autoencoder for Hyperspectral Band Reduction”, Optik, vol. 180, (IF. 2.84), 2019.

20. M. Ahmad, et.al., “Smartwatch-based Legitimate User Identification for Cloud-based Secure Services”, Journal of Mobile Information Systems, vol. 2018, (IF. 1.863), 2018.

21. M. Ahmad, et.al., “Fuzziness-based Active Learning Framework to Enhance Hyperspectral Image Classification Performance for Discriminative and Generative Classifiers”, PlosOne, vol. 13(1), (IF 3.752), 2018.

22. M. Ahmad, et.al., “Metric Similarity Regularizer to Enhance the Optimization Performance for Hyperspectral Unmixing”, Optik, vol. 140(C), (IF. 2.84), 2017.

23. M. Ahmad, et.al., “Graph-based Spatial-Spectral Feature Learning for Hyperspectral Image Classification”, IET Image Processing, vol. 11(12), (IF. 2.373), 2017.

Collaborations at National and International Level

Detail of Funded Projects

An Automated Tool to Assist Batch Advisors, 530,000 Pkr.