Note: Student's access to core academic research is crucial for the development of science. If you are a student, and you don't have access to my articles through your university subscription, email me, I will be happy to send you a pre-print version of the paper on a case by case basis.
1)J. M. P. Czarnecki, S. Samiappan, M. Zhou, C. D. McCraine, and L. L. Wasson (2021). \Real-Time Automated Classication of Sky Conditions Using Deep Learning and Edge Computing". In: Remote Sensing 13.19. url: https://www.mdpi.com/2072-4292/13/19/3859
2) M. Zhou, J. A. Elmore, S. Samiappan, K. O. Evans, M. B. Pfeier, B. F. Blackwell, and R. B. Iglay (2021). \Improving Animal Monitoring Using Small Unmanned Aircraft Systems (sUAS) and Deep Learning Networks". In: Sensors 21.17. url: https://www.mdpi.com/1424-8220/21/17/5697
3) J. A. Elmore, M. F. Curran, K. O. Evans, S. Samiappan, M. Zhou, M. B. Pfeier,B. F. Blackwell, and R. B. Iglay (2021-06). \Evidence on the effectiveness of small unmanned aircraft systems (sUAS) as a survey tool for North American terrestrial, vertebrate animals: a systematic map protocol". In: Environmental evidence 10.1, p. 15. url: https://doi.org/10.1186/s13750-021-00228-w
4) S. Sawant, P. Manoharan, S. Samiappan, et.al "A modified Cuckoo Search algorithm based optimal band subset selection approach for hyperspectral image classification" [link]
5) A. Shamaskin, S. Samiappan, et al “Multi-attribute Ecological and Socioeconomic Geodatabase for the Gulf of Mexico Coastal Region of the United States”, MDPI Data, December 2019
6) S. Samiappan, C. McCraine, et al “Remote Sensing of Wildfire using a small Unmanned Aerial System: Post-fire Mapping, Vegetation recovery and damage analysis in Grand Bay, Mississippi/Alabama, U.S” MDPI Drones, April 2019 [link]
7) P. Burr, S. Samiappan, et.al “Estimating the Distribution and Abundance of Water Birds on Catfish Aquaculture Facilities Using Imagery Collected from an Unmanned Aerial System” Human-Wildlife Interactions 2019 August 2019 [link]
8) S. Samiappan., A. Shamaskin, et.al Land Conservation in the Gulf of Mexico Region: A Comprehensive Review of Plans, Priorities, and Efforts. MDPI Land, May 2019 [link]
9) P. Manoharan, S. Sawant, S. Samiappan, et.al “Three-dimensional discrete cosine transform-based feature extraction for hyperspectral image classification” Journal of Applied Remote Sensing, 2018 [link]
10) S. Samiappan, J. Czarnecki, et al “Quantifying Damage from Wild Pigs with Small Unmanned Aerial Systems” Wildlife Society Bulletin, January 2017 [link]
11) S. Samiappan., G. Turnage, C. McCraine, et.al “Post-Logging Estimation of Loblolly Pine (Pinus Taeda) Stump Size, Area and Population Using Imagery from a Small Unmanned Aerial System”. MDPI Drones, 2017. [link]
12) J. Czarnecki, S. Samiappan, et.al “Applications of unmanned aerial vehicles in weed science” Advances in animal biosciences: Precision Agriculture, Cambridge University Press 2017 [link]
13) S. Samiappan, G. Turnage, L. Hathcock, et.al “Mapping of Invasive Phragmites (common reed) in Gulf of Mexico Coastal Wetlands using Multispectral Imagery and Unmanned Aerial Systems” International Journal of Remote Sensing, December 2016 [link]
14) S. Samiappan, G. Turnage, L. Hathcock, et.al “Using Unmanned Aerial Vehicles for High-Resolution Remote Sensing to Map Invasive Phragmites australis in Coastal Wetlands” International Journal of Remote Sensing, October 2016 [link]
15) S. Samiappan, S. Prasad, and L. Bruce, “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, April 2013 [link]
16) B. Sridhar, I. A. Sheriff, K.A.N. Kutty, and S. Samiappan “Comparison of Cascaded LMS-RLS, LMS and RLS Adaptive Filters in Non-Stationary Environments”, Springer Novel Algorithms and Techniques in Telecommunications and Networking, May 2010 [link]
1) M. Zhou, S. Samiappan, E. Worch, J. E. Ball “Hyperspectral image classification using fisher’s linear discriminant analysis feature reduction with Gabor filtering and CNN” IEEE International Geoscience and Remote Sensing Symposium, Hawaii, USA July 2020.
2) E. Worch, S. Samiappan, M. Zhou, J. E. Ball “Hyperspectral band selection using Moth-Flame metaheuristic optimization” IEEE International Geoscience and Remote Sensing Symposium, Hawaii, USA July 2020.
3) S. Samiappan, A. Shamaskin, et. al “Strategic conservation of Gulf coast landscapes using multi-criteria decision analysis and open source remote sensing and GIS data” IEEE International Geoscience and Remote Sensing Symposium, Hawaii, USA July 2020.
4) S. Sawant, P. Manoharan, S. Samiappan “A band selection method for hyperspectral image classification based on cuckoo search algorithm with correlation based initialization” Proceedings of the IEEE Workshop on Hyperspectral Image and Signal Processing, Amsterdam, Netherlands, September 2019
5) J. Czarnecki, S. Samiappan, L. Hathcock “The application of structure from motion techniques in late-season corn damage” Proceedings of Precision Agriculture, Montpellier, France 2019
6) C. McCraine, S. Samiappan, J. Czarnecki et.al “Plant density estimation and weeds mapping on row crops at emergence using low altitude UAS imagery” Proceedings of SPIE Defense + commercial sensing – Autonomous air and ground sensing for agricultural optimization and phenotyping, Baltimore, Maryland, April 2019 [link]
7) P. Manoharan, S. Sawant, S. Samiappan, et.al “Ranking and grouping based feature selection for hyperspectral image classification” Proceedings of Asian conference on Remote Sensing, Kula Lumpur, Malaysia 2018
8) S. Samiappan, L. Casagrande, and G.M.Machado et. al “Texture classification of Very High Resolution UAS Imagery Using a Graphics Processing Unit” IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain July 2018
9) L. Casagrande, G.M.Machado, S. Samiappan et al “Probabilistic Neural Network and Wavelet Transform for Mapping of Phragmites australis using Low Altitude Remote Sensing” ACM SIBGRAPI - Conference on Graphics, Patterns and Images Niteroi, Brazil, October 2017 [link]
10) R. Moorhead, J. Czarnecki, S. Samiappan et al “Swimming in sensors and drowning in data: What is needed for UASs to be effective” Proceedings of SPIE Autonomous air and ground sensing systems for agricultural optimization and phenotyping, Anaheim, California, April 2017 [link]
11) S. Samiappan, G.Turnage, L.Hathcock, et al “Classifying common wetland plants using hyperspectral data to identify optimal spectral bands for species mapping using a small unmanned aerial systems– a case study” IEEE International Geoscience and Remote Sensing Symposium, Fort Worth TX, July 2017 [link]
12) J. Czarnecki, S. Samiappan, et.al “Applications of unmanned aerial vehicles in weed science” 11th European Conference on Precision Agriculture. July 16-20, 2017, Edinburgh, Scotland, Cambridge University Press [link]
13) S. Samiappan, L. Dabbiru and R. Moorhead “Fusion Of Hyperspectral And Lidar Data Using Random Feature Selection And Morphological Attribute Profiles” 8th IEEE Workshop on Hyperspectral Image and Signal Processing, Los Angeles, CA, August 2016 [link]
14) S. Samiappan and R. Moorhead, “Semi-Supervised Co-Training and Active Learning Framework for Hyperspectral Image Classification” IEEE International Geoscience and Remote Sensing Symposium, Milan, Italy June 2015 [link]
15) L. Dabbiru, S. Samiappan, R. Nobrega, et.al “Fusion of Synthetic Aperture Radar and Hyperspectral Imagery to Detect Impacts of Oil Spill in Gulf of Mexico” IEEE International Geoscience and Remote Sensing Symposium, Milan, Italy June 2015 [link]
16) J. Ball, D. Anderson, and S. Samiappan, “Hyperspectral Band Selection Based on the Aggregation of Proximity Measures for Automated Target Detection”, SPIE Conference - DSS, Baltimore, ML April 2014 [link]
17) S. Samiappan, L. Bruce, and H. Yao, “Support Vector Machines Classification of Fluorescence Hyperspectral Image for Detection of Aflatoxin in Corn Kernels” IEEE Workshop on Hyperspectral Image & Signal Processing: Evolution in Remote Sensing July 25, 2013 [link]
18) S. Samiappan, L. Bruce, and S. Prasad, “Automated Hyperspectral Imagery Analysis via Support Vector Machines based Multi-Classifier System with Non-Uniform Random Feature Selection”, Proceedings of the IEEE Geoscience and Remote Sensing Symposium, Vancouver, Canada. July 5, 2011 [link]
19) S. Samiappan, L. Bruce, and S. Prasad, “Branch and Bound based Feature Elimination for Support Vector Machine based Classification of Hyperspectral Images”, Proceedings of the IEEE Geoscience and Remote Sensing Symposium, Vancouver, Canada. July 5, 2011 [link]
20) S. Samiappan, S. Prasad, and L. Bruce, “NASA's Upcoming HyspIRI Mission - Precision Vegetation Mapping with Limited Ground Truth” Proceedings of the IEEE Geoscience and Remote Sensing Symposium. Honolulu, Hawaii, USA June 2010 [link]
21) S. Prasad, H. Kalluri, L. Bruce, S. Samiappan “Data Dependent Adaptation for Improved Classification of Hyperspectral Imagery”, Proceedings of the IEEE Geoscience and Remote Sensing Symposium. Honolulu, Hawaii, USA June 2010 [link]
22) B. Arumugam, S. Samiappan, and P. Manoharan, “Improved Adaptive Skip Algorithm for Video Shot Boundary Detection”, Proceedings of the IEEE International Conference on Signal Processing, Communications and Networking, Chennai, February 5, 2007 [link]
1) J. Liu, A. Shamaskin, S. Samiappan et al “Dynamic Rshiny Applications to Support Gulf of Mexico Land Conservation” American Fisheries Society and The Wildlife Society 2019 Joint Annual Conference, Reno, NV, September 28, 2019.
2) A. Shamaskin, K. Evans, S. Samiappan et al “Valuing land conservation to support estuarine biotic health in the Gulf of Mexico – a Hierarchical Approach” American Fisheries Society and The Wildlife Society 2019 Joint Annual Conference, Reno, NV, September 28, 2019.
3) S. Samiappan., A. Shamaskin, et.al “Science-Based Land Conservation Prioritization Framework: An Overview” Mississippi Water Resource Conference, Jackson, MS, April 2-3 2019.
4) Turnage, G., S. Samiappan, L. Hathcock, and R. J. Moorhead. 2018. “Detection of aquatic plant species using UAS technology”. 15th International Symposium on Aquatic Plants, Queenstown, New Zealand, February 18 – 23, 2018.
5) C. McCraine, S. Samiappan, G. Turnage, L. Hathcock, H. Yao, R. Kincaid, R. Moorhead, and S. Ashby. 2018. Classifying common aquatic plants using hyperspectral data to identify optimal spectral bands for species mapping using a small unmanned aerial system – a case study. Presented at the Society of Lake Management Professionals annual conference, Baton Rouge, LA, January 22-25, 2018
6) S. Samiappan, C. McCraine, L.Hathcock, et.al “Wildfire Mapping and Damage Analysis in Grand Bay National Estuarine Research Reserve, Mississippi Using a Small Unmanned Aerial System with a Multispectral Payload” Presented at 2016 The Wildlife Society annual conference, Albuquerque, NM, September 2017.
7) G. Turnage, S. Samiappan, L. Hathcock, R. Moorhead “Mapping of Phragmites australis using 5-band imagery collected from an Unmanned Aerial System” Presented at 2016 The Wildlife Society annual conference, Raleigh, NC, October 2016.
8) S. Samiappan, A. Crain, and L. Hathcock, et.al “Identification and Estimation of Damage caused by Feral Hogs in Corn Fields using Change Detection and an Unmanned Aerial System” presented at The Wildlife Society annual conference, Raleigh, NC, October 2016.
9) P. Burr, S. Samiappan, and L. Hathcock, et.al “Estimating the Distribution and Abundance of Water Birds on Catfish Aquaculture Facilities Using Imagery Collected from an Unmanned Aerial System” presented at The Wildlife Society annual conference, Raleigh, NC, October 2016.
10) G. Turnage, S. Samiappan, and L. Hathcock, et.al “Mapping of Phragmites australis using 5-band Imagery Collected from an Unmanned Aerial System” Presented at Midsouth Aquatic Plant Management Society conference, Baton Rouge LA September 2016.
11) S. Samiappan, G. Turnage, and R. Moorhead “Identifying and Mapping Chinese Tallow Tree Using Unmanned Aerial Systems and Multispectral Imagery” Presented at Midsouth Aquatic Plant Management Society conference, Baton Rouge LA September 2016.
12) S. Samiappan, B.W Henry and R. Moorhead “Plant stand count and corn crop density assessment using texture analysis on visible imagery collected using unmanned aerial vehicles” presented at the 13th International conference on Precision Agriculture, St.Louis, MO July 2016,
13) S. Samiappan and R.Moorhead “Mapping of Phragmites Australis in Gulf Of Mexico Wetlands Using Small UAS” Presented at the Gulf of Mexico Oil Spill and Ecosystem Science conference, Tampa, FL February 2016
14) M. Hock, W.B. Henry, and S. Samiappan, et.al “Evaluating Texture Modelling Techniques to Determine Stand Establishment and Plant Populations in Corn”. Presented at South branch American society of Agronomy, Houston TX. 2016
15) G.Turnage, P.Stinson and S. Samiappan “Mapping of Common Reed (Phragmites Australis) Using Unmanned Aerial Vehicles, Gray Level Co-Occurrence Matrix Texture Extraction, and eCogntion” Presented at Midsouth Aquatic Plant Management Society conference, Mobile AL September 2015.
16) K. Grissom, S. Samiappan, R. Beets, D. Petraitis, and Z. Zhou “Improvements to the TAO web-based Data Management System”, NOAA's 38th Climate Diagnostics and Prediction Workshop August 21, 2013
1) S. Samiappan “Mapping of invasive phragmites in the pearl river coastal wetlands and the results of its eradication efforts” June 2016 Geosystems Research Institute May 2015
2) S. Samiappan “Evaluation of unmanned aerial vehicles (UAV’s) for estimating distribution and abundance of water birds on catfish aquaculture facilities. NWRC December 2015
3) S. Samiappan “Evaluation of Unmanned Aerial Vehicles (UAV’s) for estimating distribution and damage of feral swine” USDA-APHIS October 2015
4) S. Samiappan “Estimation of plant stands on corn hybrids from UAS imagery using color segmentation and template matching algorithms” PrecisionHawk May 2015
Doctoral: Spectral band selection for ensemble classification of hyperspectral images with applications to agriculture and food safety
Master’s: Extraction of saliency regions using human visual attention model