1. Khan, M. U., ur Rehman, M. M., Sultan, M., Rehman, T. U., Sajjad, U., Yousaf, M., & Asif, M. (2022). Key prospects and major development of hydrogen and bioethanol production. International Journal of Hydrogen Energy, 47(62), 26265. https://doi.org/10.1016/j.ijhydene.2022.06.224
2. Rehman, T. U., Zhang, L., Ma, D., & Jin, J. (2022). Common Latent Space Exploration for Calibration Transfer across Hyperspectral Imaging-Based Phenotyping Systems. Remote Sensing, 14(2), 319. https://doi.org/10.3390/rs14020319
3. Ma, , Rehman, T. U., Zhang, L., Maki, H., Tuinstra, M. R., & Jin, J. (2021). Modeling of Environmental Impacts on Aerial Hyperspectral Images for Corn Plant Phenotyping. Remote Sensing, 13(13), 2520. https://doi.org/10.3390/rs13132520
4. Ma, , Rehman, T. U., Zhang, L., Maki, H., Tuinstra, M. R., & Jin, J. (2021). Modeling of diurnal changing patterns in airborne crop remote sensing images. Remote Sensing, 13(9), 1719. https://doi.org/10.3390/rs13091719
5. Rehman, T. U., Ma, D., Wang, L., Zhang, L., & Jin, J. (2020). Predictive spectral analysis using an end-to-end deep model from hyperspectral images for high-throughput plant phenotyping. Computers and Electronics in Agriculture, 177, 105713. https://doi.org/10.1016/j.compag.2020.105713
6. Rehman, T. U., Zhang, L., Ma, D., Wang, L., & Jin, J. (2020). Calibration transfer across multiple hyperspectral imaging-based plant phenotyping systems: I–Spectral space adjustment. Computers and Electronics in Agriculture, 176, 105685. https://doi.org/10.1016/j.compag.2020.105685
7. Rehman, T. U., Zhang, L., Wang, L., Ma, D., Maki, H., Sánchez-Gallego, J. A., Mickelbart, M. V., & Jin, J. (2020). Automated leaf movement tracking in time-lapse imaging for plant phenotyping. Computers and Electronics in Agriculture, 175, 105623. https://doi.org/10.1016/j.compag.2020.105623
8. Wang, L., Jin, J., Song, Z., Wang, J., Zhang, L., Rehman, T. U., Ma, D., Carpenter, N., & Tuinstra, M. R. (2020). LeafSpec: An accurate and portable hyperspectral corn leaf imager. Computers and   Electronics   in   Agriculture, 169, https://doi.org/10.1016/j.compag.2019.105209
9. Wang, L., Duan, Y., Zhang, L.,Rehman, T. U., Ma, D., & Jin, J. (2020). Precise Estimation of NDVI with a Simple NIR Sensitive RGB Camera and Machine Learning Methods for Corn Plants. Sensors, 20(11), 3208. https://doi.org/10.3390/s20113208

10. Zhang, , Wang, L., Wang, J., Song, Z., Rehman, T. U., Bureetes, T., Ma, D., Chen, Z., Neeno S., & Jin, J. (2019). Leaf Scanner: A portable and low-cost multispectral corn leaf scanning device for precise phenotyping. Computers and Electronics in Agriculture, 167, 105069. https://doi.org/10.1016/j.compag.2019.105069
11. Khan, M. U., & Rehman, T. U. (2019). Early trends, current status and future prospects of farm mechanization in Agricultural Engineering International: CIGR Journal, 21(3), 76-87.
12. Ma, D., Carpenter, N., Maki, H., Rehman, T. U., Tuinstra, M. R., & Jin, J. (2019). Greenhouse environment modeling and simulation for microclimate control. Computers and electronics in agriculture, 162, 134-134. https://doi.org/10.1016/j.compag.2019.04.013

13. Rehman, T. U., Zaman, Q. U., Chang, Y. K., Schumann, A. W., & Corscadden, K. W. (2019). Development and field evaluation of a machine vision based in-season weed detection system for wild Computers and Electronics in Agriculture, 162, 1-13. https://doi.org/10.1016/j.compag.2019.03.023
14. Zhang, L., Maki, H., Ma, D., Sánchez-Gallego, J. A., Mickelbart, M. V., Wang, L., Rehman, T. U., & Jin, J. (2019). Optimized angles of the swing hyperspectral imaging system for single corn plant. Computers and electronics in agriculture, 156, 349-359. https://doi.org/10.1016/j.compag.2018.11.030
15. Rehman, T. U., Mahmud, M. S., Chang, Y. K., Jin, J., & Shin, J. (2019). Current and future applications of statistical machine learning algorithms for agricultural machine vision Computers  and  electronics  in  agriculture, 156,  585-605. https://doi.org/10.1016/j.compag.2018.12.006

16. Rehman, T. U., Zaman, Q. U., Chang, Y. K., Schumann, A. W., Corscadden, K. W., & Esau, T. J. (2018). Optimising the parameters influencing performance and weed (goldenrod) identification accuracy of colour co-occurrence matrices. Biosystems Engineering, 170, 85-95. https://doi.org/10.1016/j.biosystemseng.2018.04.002
17. Chang, K., Zaman, Q. U., Rehman, T. U., Farooque, A. A., Esau, T., & Jameel, M.
18. (2017). A real-time ultrasonic system to measure wild blueberry plant height during harvesting. Biosystems engineering, 157, 35-44. https://doi.org/10.1016/j.biosystemseng.2017.02.004

18. Rehman, T. U., Khan, M. U., Tayyab, M., Akram, M. W., & Faheem, M. (2016). Current status and overview of farm mechanization in Pakistan–A review. Agricultural Engineering International: CIGR Journal, 18(2), 83-93.
19. Ghafoor, A., Rehman, T. U., Munir, A., Ahmad, M., & Iqbal, M. (2016). Current status and overview of renewable energy potential in Pakistan for continuous energy sustainability. Renewable and  Sustainable  Energy  Reviews, 60,  1332-1342. https://doi.org/10.1016/j.rser.2016.03.020

Submitted Manuscripts

1. Rehman, T. U., Zhang, L., Ma, D., & Jin, J. Deep adversarial domain adaptation for calibration transfer among plant phenotyping systems. Biosystems Engineering (Under review).
2. Zhang, , Jin, J., Wang, L., Rehman, T. U., Ma, D., & Gee, T. M. Eliminating crop leaf angle impacts on plant reflectance using fusion of hyperspectral images and 3D point clouds. Computers and Electronics in Agriculture (Under review).

 Book Chapters

1. Chang, K., & Rehman, T. U. (2017). Current and future applications of cost-effective smart cameras in agriculture. In Robotics and Mechatronics for Agriculture (pp. 75-120). CRC Press.
2. Jin, J., Rehman, T. U., & Zhang, Q. (2022). Advances in optical analysis for crop phenotyping. In Advances in Plant Phenotyping for More Sustainable Crop Production (pp. 61-97). Burleigh Dodds Science Publishing Ltd.