Shridhar, B., Sheriff, A., Narayanankutty, K. A., & Samiappan, S. (2010). Comparison of Cascaded LMS-RLS, LMS and RLS Adaptive Filters in Non-Stationary Environments. Springer Novel Algorithms and Techniques in Telecommunications and Networking. Springer. [Document Site]

Matese, A., Prince Czarnecki, J. M., Samiappan, S., & Moorhead, R. J. (2023). Are Unmanned Aerial Vehicle-based Hyperspectral Imaging and Machine Learning Advancing Crop Science? Trends in Plant Science. na, 14. DOI:10.1016/j.tplants.2023.09.001.

Bheemanahalli, R., Adeli, A., Samiappan, S., Prince Czarnecki, J. M., McCraine, C., Reddy, R., & Moorhead, R. J. (2023). Phenological Stage and Vegetation Index for Predicting Corn Yield under Rainfed Environments. Frontiers in Plant Science. 14, 12. DOI:10.3389/fpls.2023.1168732.

Jones, L. R., Elmore, J. A., Samiappan, S., Evans, K. O., Pfeiffer, M. B., Blackwell, B. F., & Iglay, R. B. (2023). Fusion of Visible and Thermal Images Improves Automated Detection and Classification of Animals for Drone Surveys. Scientific Reports. 13, 10385. DOI:https://doi.org/10.1038/s41598-023-37295-7E. [Document Site]

Ramamoorthy, P., Samiappan, S., Wubben, M. J., Brooks, J. P., Panda, R. M., Reddy, R., & Bheemanahalli, R. (2022). Hyperspectral Reflectance and Machine Learning Approaches for the Detection of Drought and Root Knot Nematode Infestation in Cotton. Remote Sensing. 14, 4021. DOI:https://doi.org/10.3390/rs14164021. [Abstract]

Bheemanahalli, R., Ramamoorthy, P., Poudel, S., Samiappan, S., Wijewardane, N., & Reddy, R. (2022). Effects of Drought and Heat Stresses during Reproductive Stage on Pollen Germination, Yield, and Leaf Reflectance Properties in Maize (Zea Mays L.). Plant Direct. Wiley. 6, e434. [Abstract]

Prince Czarnecki, J. M., Samiappan, S., Zhou, M., McCraine, C., & Wasson, L. L. (2021). Real-Time Automated Classification of Sky Conditions Using Deep Learning and Edge Computing. Remote Sensing. MDPI. 13(19), 3859. DOI:/10.3390/rs13193859. [Abstract] [Document Site]

Zhou, M., Elmore, J. A., Samiappan, S., Evans, E. O., Pfeiffer, M. B., Blackwell, B. F., & Iglay, R. B. (2021). Improving Animal Monitoring Using Small Unmanned Aircraft Systems (SUAS) and Deep Learning Networks. Sensors. MDPI. 21(17), 5697. DOI:10.3390/s21175697. [Abstract] [Document Site]

Elmore, J. A., Curren, M. F., Evans, K. O., Samiappan, S., & Zhou, M. (2021). Evidence on the Effectiveness of Small Unmanned Aircraft Systems (SUAS) as a Survey Tool for North American Terrestrial, Vertebrate Animals: a Systematic Map Protocol. Environmental Evidance. Springer. 10(15), 1-6. [Abstract] [Document Site]

Sawant, S. S., Prabukumar, M., & Samiappan, S. (2020). A Modified Cuckoo Search Algorithm Based Optimal Band Subset Selection Approach for Hyperspectral Image Classification. Journal of Spectral Imaging. 9, a6. [Abstract] [Document Site]

Shamaskin, A., Samiappan, S., Liu, J., Linhoss, A., & Evans, K. O. (2019). Multi-Attribute Ecological and Socioeconomic Geodatabase for the Gulf of Mexico Coastal Region of the United States. MDPI Data. MDPI. 5(1), NA. DOI:10.3390/data5010003. [Abstract] [Document Site]

Samiappan, S., McCraine, C., Hathcock, L. A., Turnage, G., Pitchford, J., & Moorhead, R. J. (2019). Remote Sensing of Wildfire Using SUAS: Post-fire Mapping, Vegetation Recovery and Damage Analysis in Grand Bay National Estuarine Research Reserve, Mississippi. Drones. 3, 43-61. DOI:10.3390/drones3020043.

Samiappan, S., Prince Czarnecki, J. M., Foster, H., Strickland, B. K., Tegt, J. L., & Moorhead, R. J. (2018). Quantifying Damage from Wild Pigs with Small Unmanned Aerial Systems. Wildlife Society Bulletin. 42(2), 304-309. DOI:10.1002/wsb.868. [Abstract]

Samiappan, S., Turnage, G., McCraine, C., Hathcock, L. A., & Moorhead, R. J. (2017). Post-Logging Estimation of Loblolly Pine (Pinus Taeda) Stump Size, Area and Population Using Imagery from a Small Unmanned Aerial System. MDPI Drones. 1(1), 15. DOI:10.3390/drones1010004.

Samiappan, S., Turnage, G., Hathcock, L. A., & Moorhead, R. J. (2017). Mapping of Invasive Phragmites (Common Reed) in Gulf of Mexico Coastal Wetlands Using Multispectral Imagery and Unmanned Aerial Systems. International Journal of Remote Sensing. Taylor and Francis. 39, 1-32. DOI:10.1080/01431161.2016.1271480.

Samiappan, S., Turnage, G., Hathcock, L. A., Casagrande, L., Stinson, P. C., & Moorhead, R. J. (2017). Using Unmanned Aerial Vehicles for High-Resolution Remote Sensing to Map Invasive Phragmites Australis in Coastal Wetlands. International Journal of Remote Sensing. Taylor and Francis. 39, 1-19. DOI:10.1080/01431161.2016.1239288.

Samiappan, S., Prasad, S., & Bruce, L.M. (2013). Non-Uniform Random Feature Selection and Kernel Density Scoring with SVM Based Ensemble Classification for Hyperspectral Image Analysis. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.. 6(02), 792-800. [Abstract] [Document] [Document Site]

Samiappan, S., Turnage, G., & Moorhead, R. J. (2016). Identifying and Mapping Chinese Tallow Using Unmanned Aerial Systems and Multispectral Imagery. 2016 Wildlife Society Conference. Raleigh, NC.

Turnage, G., Samiappan, S., Hathcock, L. A., & Moorhead, R. J. (2016). Mapping of Phragmites Australis Using 5-band Imagery Collected from an Unmanned Aerial System. Midsouth Aquatic Plant Management Society conference. Baton Rouge, LA.

Samiappan, S., Turnage, G., & Moorhead, R. J. (2016). Identifying and Mapping Chinese Tallow Using Unmanned Aerial Systems and Multispectral Imagery. 35th Annual MidSouth Aquatic Plant Management Society Meeting. Baton Rouge, LA.

Samiappan, S., Turnage, G., Hathcock, L. A., & Moorhead, R. J. (2016). Mapping of Phragmites Australis in Gulf of Mexico Wetlands Using Small UAS. 2016 Gulf of Mexico Oil Spill & Ecosystem Science Conference Proceedings. Tampa, FL: GOMRI. [Abstract]

Stinson, P. C., Casagrande, L., Turnage, G., Samiappan, S., Hathcock, L. A., & Moorhead, R. J. (2015). Mapping of Common Reed (Phragmites Australis) Using Unmanned Aerial Vehicles, Gray Level Co-Occurrence Matrix Texture Extraction, and ECognition. Midsouth Aquatic Plant Society Meeting. Mobile, AL.

Samiappan, S., Zhou, M., Bheemanahalli, R., Brooks, J., & Wubben, M. (2021). Early Detection of Root-Knot Nematode (Meloidogyne Incognita) Infestation in Cotton Using Hyperspectral Data. Proceedings of 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. Brussels, Belgium: IEEE. DOI:10.1109/IGARSS47720.2021.9554055. [Abstract] [Document Site]

Zhou, M., Samiappan, S., Worch, E., & Ball, J. E. (2020). Hyperspectral Image Classification Using Fisher's Linear Discriminant Analysis Feature Reduction with Gabor Filtering and CNN. Proceedings of 2020 IEEE International Geoscience and Remote Sensing Symposium. Waikoloa, HI, USA: IEEE. DOI:10.1109/IGARSS39084.2020.9323727. [Abstract] [Document Site]

Worch, E., Samiappan, S., Zhou, M., & Ball, J. E. (2020). Hyperspectral Band Selection Using Moth-Flame Metaheuristic Optimization. Proceedings of 2020 IEEE International Geoscience and Remote Sensing Symposium. Waikoloa, HI, USA: IEEE. DOI:10.1109/IGARSS39084.2020.9323754. [Abstract] [Document Site]

Samiappan, S., Shamaskin, A., Linhoss, A., Evans, K. O., & Liu, J. (2020). Strategic Conservation of Gulf Coast Landscapes Using Multi-Criteria Decision Analysis and Open Source Remote Sensing and GIS Data. Proceedings of 2020 IEEE International Geoscience and Remote Sensing Symposium. Waikoloa, HI, USA: IEEE. DOI:10.1109/IGARSS39084.2020.9323166. [Abstract] [Document Site]

Sawant, S., Prabukumar, M., & Samiappan, S. (2019). A Band Selection Method For Hyperspectral Image Classification Based On Cuckoo Search Algorithm With Correlation Based Initialization. Proceedings of 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). Amsterdam, Netherlands: IEEE. DOI:10.1109/WHISPERS.2019.8920950. [Abstract] [Document Site]

Prince Czarnecki, J. M., Samiappan, S., & Hathcock, L. A. (2019). The Application of Structure from Motion Techniques in Late-season Corn Damage. In John V. Stafford (Ed.), Precision Agriculture '19. Montpellier, France: Wageningen Academic Publishers. 405-411. DOI:10.3920/978-90-8686-888-9_50. [Abstract]

Samiappan, S., Turnage, G., Hathcock, L. A., & Moorhead, R. J. (2017). Probabilistic Neural Network and Wavelet Transform for Mapping of Phragmites Australis Using Low Altitude Remote Sensing. Proceedings of IEEE SIBGRAPI. Niteroi, Brazil. DOI:10.1109/SIBGRAPI.2017.42.

Prince Czarnecki, J. M., Samiappan, S., Wasson, L. L., McCurdy, J. D., Reynolds, D., Williams, W. P., & Moorhead, R. J. (2017). Applications of Unmanned Aerial Vehicles in Weed Science. Advances in Animal Biosciences: Precision Agriculture (ECPA) 2017. Edinburgh, Scotland. 8(2), 807-811. DOI:10.1017/S2040470017001339.

Samiappan, S., Turnage, G., Hathcock, L. A., Yao, H., Kincaid, R., Moorhead, R. J., & Ashby, S. (2017). Classifying Common Wetland Plants Using Hyperspectral Data To Identify Optimal Spectral Bands For Species Mapping Using A Small Unmanned Aerial Systems- A Case Study. Proceedings of IEEE IGARSS. Fort Worth, TX.

Turnage, G., Samiappan, S., Hathcock, L. A., & Moorhead, R. J. (2016). Mapping of Phragmites Australis Using 5-band Imagery Collected from an Unmanned Aerial System. Wildlife Society\'s 23rd Annual Conference. Raleigh, NC.

Burr, P., Samiappan, S., Hathcock, L. A., Dorr, B., & Moorhead, R. J. (2016). Estimating the Distribution and Abundance of Water Birds on Catfish Aquaculture Facilities Using Imagery Collected from an Unmanned Aerial System. Wildlife Society's 23rd Annual Conference. Raleigh, NC.

Samiappan, S., Dabbiru, L., & Moorhead, R. J. (2016). Fusion of Hyperspectral and LiDAR Data Using Random Feature Selection and Morphological Attribute Profiles. WHISPERS. Los Angeles, CA: 8th Workshop on hyperspectral image and signal processing: Evolution in Remote Sensing. [Abstract]

Dabbiru, L., Samiappan, S., Nobrega, R. A. A., Aanstoos, J.V., Younan, N. H., & Moorhead, R. J. (2015). Fusion of Synthetic Aperture Radar and Hyperspectral Imagery to Detect Impacts of Oil Spill in Gulf of Mexico. IGARSS 2015 proceedings. Milan, Italy: IEEE.

Samiappan, S., & Moorhead, R. J. (2015). Semi-Supervised Co-Training and Active Learning Framework for Hyperspectral Image Classification. IGARSS 2015 Proceedings. Milan, Italy: IEEE. [Document]

Ball, J. E., Anderson, D., & Samiappan, S. (2014). Hyperspectral Band Selection Based on the Aggregation of Proximity Measures for Automated Target Detection. SPIE. SPIE Conference - DSS, Baltimore, Maryland. [Document Site]

Samiappan, S., Bruce, L.M., Yao, H., Hruska, Z., Kincaid, R., Brown, R. L., Bhatnagar, D., & Cleveland, T. E. (2013). Support Vector Machines Classification of Fluorescence Hyperspectral Image for Detection of Aflatoxin in Corn Kernels. Proceedings of IEEE 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing Conference. Gainesville, FL.

Samiappan, S., Prasad, S., Bruce, L.M., & Hansen, E. (2011). Branch and Bound Based Feature Elimination for Support Vector Machine Based Classification of Hyperspectral Images. IEEE Geoscience and Remote Sensing Symposium. Proceedings of the IEEE Geoscience and Remote Sensing Symposium, Vancouver, Canada.

Samiappan, S., Prasad, S., & Bruce, L.M. (2011). Automated Hyperspectral Imagery Analysis via Support Vector Machines Based Multi-Classifer System with Non-Uniform Random Feature Selection. IEEE Geoscience and Remote Sensing Symposium. Proceedings of the IEEE Geoscience and Remote Sensing Symposium, Vancouver, Canada.

Samiappan, S., Prasad, S., & Bruce, L.M. (2010). NASA's Upcoming HyspIRI Mission - Precision Vegetation Mapping with Limited Ground Truth. Proceedings of the IEEE Geosciene and Remote Sensing Symposium (IGARSS). Honolulu, Hawaii. [Document Site]

Samiappan, S., Crain, A., Hathcock, L. A., Cunningham, F., & Moorhead, R. J. (2016). Identification and Estimation of Damage Caused by Feral Hogs in Corn Fields Using Change Detection and an Unmanned Aerial System. Wildlife Society's 23rd Annual Conference. Raleigh, NC.

Samiappan, S., Henry, B., & Moorhead, R. J. (2016). Plant Stand Count and Corn Crop Density Assessment Using Texture Analysis on Visible Imagery Collected Using Unmanned Aerial Vehicles. 13th International Conference on Precision Agriculture. St. Louis, MO.

Linhoss, A., Prince Czarnecki, J. M., & Samiappan, S. (2019). Remotely Sensing Sediment Tracers. Mississippi Water Resources Conference. Jackson, MS. [Abstract]

McCraine, C., Samiappan, S., Prince Czarnecki, J. M., & Dodds, D. M. (2019). Plant Density Estimation and Weeds Mapping on Row Crops at Emergence Using Low Altitude UAS Imagery. Proceedings Volume 11008, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping IV. Baltimore, MD: Society of Photo-Optical Instrumentation Engineers. 11008, 110080Y. DOI:10.1117/12.2520252. [Abstract]

Moorhead, R. J., Prince Czarnecki, J. M., Samiappan, S., & Henry, W. B. (2017). Swimming in Sensors and Drowning in Data: What Is Needed for UASs to Be Effective? Proceedings Volume 10218, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping II. Anaheim, CA: Society of Photo-Optical Instrumentation Engineers (SPIE). 102180L. DOI:10.1117/12.2267721. [Abstract]

Dabbiru, L., Samiappan, S., Aanstoos, J.V., & Moorhead, R. J. (2016). Fusion of Synthetic Aperture Radar and Hyperspectral Imagery to Detect Impacts of Oil Spill in Gulf of Mexico. Naval Oceanographic Office 4th Annual Operational Oceanography Science and Technology Poster Symposium. Stennis Space Center, MS. [Abstract] [Document]

Henry, W. B., Fox, A.A.A., Moorhead, R. J., Samiappan, S., Whittenton, J. B., Hock, M. W., & Prince Czarnecki, J. M. (2016). In-Field UAV Corn Phenotyping: a High Throughput Model. Annual Joint Meeting of the Southern Association of Agricultural Scientists/Southern Regional Branch of the American Society of Agronomy. San Antonio, TX.

Samiappan, S., Turnage, G., Hathcock, L. A., & Moorhead, R. J. (2016). Mapping of Invasive Phragmites in the Pearl River Coastal Wetlands and the Results of Its Eradication Efforts. Mississippi State University: Geosystems Research Institute. [Document]