Chorney, W., Rahman, A., Wang, Y., Wang, H., & Peng, Z. (2025). Federated Learning for Heterogeneous Multi-Site Crop Disease Diagnosis. Mathematics, 13(9), 1401. [Paper]
Rahman, A., Street, J., Wooten, J., Marufuzzaman, M., Wang, H., Gude, V. G., & Buchanan, R. (2024). Interpretable Wood Chip Moisture Content Prediction Through Texture Analysis, Expert Systems with Applications, 126989. [Paper] [Code]
Rahman, A., He, L., & Wang, H. (2024). Activation function optimization scheme for image classification. Knowledge-Based Systems, 112502. [Paper] [Code]
Rahman, A., Street, J., Wooten, J., Marufuzzaman, M., Gude, V. G., Buchanan, R., & Wang, H. (2024). MoistNet: Machine vision-based deep learning models for wood chip moisture content measurement. Expert Systems with Applications, 125363. [Paper]
Rahman, A., Marufuzzaman, M., Street, J., Wooten, J., Gude, V. G., Buchanan, R., & Wang, H. (2024). A comprehensive review on wood chip moisture content assessment and prediction. Renewable and Sustainable Energy Reviews, 189, 113843. [Paper]
Wang, Y., Rahman, A., Duggar, W. N., Thomas, T. V., Roberts, P. R., Vijayakumar, S., ... & Wang, H. (2023). A gradient mapping guided explainable deep neural network for extracapsular extension identification in 3D head and neck cancer computed tomography images. Medical Physics. [Paper]
Duggar, W. N., Thomas, T. V., Wang, Y., Rahman, A., Wang, H., Roberts, P. R., ... & Vijayakumar, S. (2023). Preoperative Prediction and Identification of Extracapsular Extension in Head and Neck Cancer Patients: Progress and Potential. Cureus, 15(2). [Paper]
Rahman, A., Lu, Y., & Wang, H. (2023). Performance evaluation of deep learning object detectors for weed detection for cotton. Smart Agricultural Technology, 3, 100126. [Paper] [Code] [Data]
Rahman, A., Marufuzzaman, M., Street, JT., Wooten, J., Gude, VG., & Wang, H. “Boosting Discriminability of Transferable Features in Unsupervised Domain Adaptation.”
Douglas, Z., Rahman, A., Duggar, W., & Wang, H. “Batch Size and Learning Rate Optimization for Three-Dimensional Medical Image Segmentation.”
Rahman, A., Ma, J., & Wang, H. “A Proximal Policy Optimization-based Reinforcement Learning Model for Multivariate Time Series Anomaly Detection.”
Rahman, A., Eskorouchi, A.*, Street, J., Wooten, J., Marufuzzaman, M., & Wang, H. “Wood Chip Moisture Content Assessment Using Infrared Image-Based Machine Learning”, in Proceedings of the ASABE International Meeting (AIM 2024), Anaheim, CA, July 28-31, 2024. [Poster]
Rahman, A., Kolla, M.*, Marufuzzaman, M., Wang, H., & Peng, Z. “Image-based Genotype Encoding for Phenotype Prediction and Exploration for Result Explainability”, In IISE Annual Conference and Expo, Montreal, Canada, May 18-22, 2024. [Paper]
Rahman, A., Chen, M.*, Lu, Y., & Wang, H. “Weed Detection in Cotton Fields Using YOLOv5: Prototype Development and Deployment”, In IISE Annual Conference and Expo, Montreal, Canada, May 18-22, 2024. [Paper]
Rahman, A., Marufuzzaman, M., & Wang, H. “An Interpretable Optimal Pricing Strategy for E-Commerce Platforms”, In IISE Annual Conference and Expo, Montreal, Canada, May 18-22, 2024. [Paper]
Rahman, A., Marufuzzaman, M., Street, J. T., Wooten, J., Gude, V. G., & Wang, H. “An Interpretable Deep Learning Model for Wood Chip Moisture Content Prediction”, In IISE Annual Conference and Expo, New Orleans, Louisiana, May 21-24, 2023. [Paper]
Rahman, A., Lu, Y., & Wang, H. (2022). “Deep Neural Networks for Weed Detections Towards Precision Weeding”, In 2022 ASABE Annual International Meeting, Houston, Texas, July 17-22, 2022. (p. 1). [Paper]
Rahman, A., Sarker, S., & Islam, M. T. (2018, December). “Simulating Cutting Line of a Furniture Industry”, In 2018 International Conference on Production and Operations Management Society (POMS), Kandy, Sri Lanka, Dec 14-16, 2018. (pp. 1-7). [Paper]
Rahman, A., Marufuzzaman, M., & Wang, H. “Boosting Discriminability of Transferable Features in Unsupervised Domain Adaptation”, IISE Annual Conference and Expo 2024, Montreal, Canada, 2024.
Chen, M.*, Nunn, D., Rahman, A., and Wang, H., “Developing a Prototype of Artificial Intelligence System for Real-time Cotton Weed Detection,” IISE Annual Conference and Expo, 2023.
Rahman, A., Chen, M.*, Nunn, D., Lu, Y., and Wang, H., “Developing a Prototype of Cost-effective Artificial Intelligence System for Real-time Cotton Weed Detection,” Beltwide Cotton Conference, 2023.
Wang, Y., Rahman, A., Duggar, W. N., Thomas, T. V., Roberts, P. R., Vijayakumar, S., Jiao, Z., Bian, L., and Wang, H. “An Explainable Deep Neural Network for Extracapsular Extension Identification in 3D Head and Neck Cancer Computed Tomography Images,” INFORMS Annual Meeting, 2023.
Rahman, A., Wang, Y., & Wang, H. “Exponential Error Linear Unit (EELU): Optimization-boosted Activation Function for Image Classification”, IISE Annual Conference and Expo, 2022.
Rahman, A., Ma, J., & Wang, H. “Multivariate Time Series Anomaly Detection through Reinforcement Learning”, ICCMAE 2022: The Second International Conference on Computational Methods and Applications in Engineering. Mississippi State, Mississippi, 2022.
Wang, Y., Rahman, A., Duggar, W. N., Thomas, T. V., Roberts, P. R., Vijayakumar, S., Jiao, Z., Bian, L., and Wang, H. “High-risk Head and Neck Cancer Evaluation with Artificial Intelligence,” 39th Annual Southern Biomedical Engineering Conference, 2022.
Rahman, A., Eskorouchi, A.*, Street, J., Wooten, J., Marufuzzaman, M., & Wang, H. “Wood Chip Moisture Content Assessment Using Infrared Image-Based Machine Learning”, ASABE International Meeting, 2024. [Poster]
Rahman, A., Marufuzzaman, M., Street, J., Wooten, J., &Wang, H. “An Interpretable Deep Learning Model for Wood Chip Moisture Content Prediction”, 2024 IISE Southeastern Regional Conference, hosted by Mississippi State University, 2024. (1st prize winner in poster presentation) [Poster]
“Boosting Discrimanility of Transferable Features in Unsupervised Domain Adaptation”, Graduate Research Symposium – Spring 2024, Mississippi State University, Mississippi State, Feb 26, 2024.
“MoistNet: Neural Architecture Search and Bayesian Optimization-driven Model for Moisture Content Prediction in Wood Chips”, Graduate Research Symposium – Fall 2023, Mississippi State University, Mississippi State, Oct 21, 2023.
“Prediction of Genotype and Phenotype Association Using Deep Learning”, Graduate Research Symposium – Fall 2023, Mississippi State University, Mississippi State, Oct 21, 2023. (3rd prize in Oral Presentation)
“An Interpretable Deep Learning Model for Wood Chip Moisture Content Prediction”, Graduate Research Symposium – Spring 2023, Mississippi State University, Mississippi State, Feb 25, 2023. (3rd prize in Oral Presentation) [News]
“Multivariate Time Series Anomaly Detection through Reinforcement Learning”, Graduate Research Symposium – Fall 2022, Mississippi State University, Mississippi State, Oct 22, 2022.
“Activation Function Optimization Scheme for Image Classification”, Graduate Research Symposium – Spring 2022, Mississippi State University, Mississippi State, Feb 26, 2022. (1st prize in Oral Presentation) [News]