Publications & Presentations

Publications

Conference Papers

  1. J. Peeples, C. McCurley, S. Walker, D. Stewart, A. Zare, 2022. “Learnable Adaptive Cosine Estimator (LACE) for Image Classification,” in IEEE/CVF Winter Conference on Applications of Computer Vision. (pdf)
  2. D. Prioleau, A. Alikhademi, A. Roberts, J. Peeples, A. Zare, J.E. Gilbert, 2021. “Use of Divisive Clustering for Reducing Bias in Training Data,” in International Conference on Machine Learning and Data Mining in Pattern Recognition. (pdf)
  3. S. Walker, J. Peeples, J. Dale, A. Zare, J. Keller, 2021. “Explainable Systematic Analysis for Synthetic Aperture Sonar Imagery,” in IEEE International Geoscience and Remote Sensing Symposium. (pdf)
  4. J. Peeples, M. Cook, D. Suen, A. Zare, J. Keller, 2019. “Comparison of Possibilistic Fuzzy Local Information C-Means and Possiblisitic K-Nearest Neighbors for Synthetic Aperture Sonar Segmentation,” in Proc. SPIE 11012, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV. (pdf)
  5. A. Starke, J. McNair, R. Trevizan, A. Bretas, J. Peeples, A. Zare, 2018. “Toward Resilient Smart Grid Communications using Distributed SDN with ML-Based Anomaly Detection,” in 16th International Conference on Wired & Wireless Internet Communications. (pdf)
  6. J. Peeples, D. Suen, A. Zare, J. Keller, 2018. “Possibilistic Fuzzy Local Information C-means with Automated Feature selection for Seafloor Segmentation,” in Proc. SPIE 10628, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII. (pdf)

Journal Papers

  1. J. Peeples, J. Jameson, N. Kotta, J. Grasman, W. Stoppel, A. Zare, 2022. “Jointly Optimized Spatial Histogram UNET Architecture (JOSHUA) for Adipose Tissue Segmentation,” in BME Frontiers Special Issue: AI for Advanced Biomedical Applications, vol. 2022, doi: 10.34133/2022/9854084. (pdf)
  2. J. Peeples, S. Walker, C. McCurley, A. Zare, J. Keller, W. Xu, 2022. “Divergence Regulated Encoder Network for Joint Dimensionality Reduction and Classification,” in IEEE Geoscience and Remote Sensing Letters. (pdf)
  3. R. Gloaguen, Z. Brym, J. Peeples, W. Xu, C. Hyen-Chung, D. Rowland, 2022. “The Plasticity of Early Root Development in Sesamum indicum L. as Influenced by Genotype and Water Availability,” in Rhizosphere. (pdf)
  4. J. Peeples, W. Xu, A. Zare, 2021. “Histogram Layers for Texture Analysis,” in IEEE Transactions on Artificial Intelligence. (pdf)

In Review

  1. J. Peeples, W. Xu, R. Gloaguen, D. Rowland, A. Zare, Z. Brym, 2021. “Spatial and Texture Analysis of Root System Architecture with Earth Mover’s Distance (STARSEED).”(pdf)

Oral Presentations

  1. J. Peeples, C. McCurley, S. Walker, D. Stewart, and A. Zare, 2022. Learnable Adaptive Cosine Estimator (LACE) for Image Classification, in IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)}, Waikoloa, HI, Virtual. (video)
  2. D. Prioleau, A. Alikhademi, A. Roberts, J. Peeples, A. Zare, J.E. Gilbert, 2021. Use of Divisive Clustering for Reducing Bias in Training Data. International Conference on Machine Learning and Data Mining in Pattern Recognition, New York City, New York, Virtual.
  3. S. Walker, J. Peeples, J. Dale, A. Zare, J. Keller, 2021. Explainable Systematic Analysis for Synthetic Aperture Sonar Imagery. IEEE International Geoscience and Remote Sensing Symposium, Brussels, Belgium, Virtual.
  4. J. Peeples, J. Jameson, N. Kotta, W. Stoppel, A. Zare, 2021. Jointly Optimized Spatial Histogram U-NET Architecture (JOSHUA) for Adipose Tissue Identification in Histological Images of Lyophilized Silk Sponge Implants. University of Florida Biomaterials Day, Gainesville, FL.
  5. R.M. Gloaguen, J. Peeples, W. Xu, Z.T. Brym, D.L. Rowland, A. Zare, H.C. Chun. 2020. New Approaches to Characterize the Root System Architecture Response of a Drought Tolerant Crop to Varying Soil Moisture Levels. ASA-CSSA-SSSA Annual Meeting, Nov. 9-13, C02 Crop Physiology and Metabolism Section, C-2 Graduate Student Oral, Virtual.
  6. J. Peeples, M. Cook, D. Suen, A. Zare, J. Keller, 2019. Comparison of Possibilistic Fuzzy Local Information C-Means and Possibilistic K-Nearest Neighbors for Synthetic Aperture Sonar Image Segmentation. Society for Optics and Photonics Defense + Commercial Sensing, Baltimore, MD.
  7. J. Peeples, 2019. Histogram Layer: A Novel Approach to Feature Engineering. McKnight Doctoral Mid-Year Research and Writing Conference, Tampa, FL.
  8. J. Peeples, D. Suen, A. Zare, J. Keller, 2018. Possibilistic Fuzzy Local Information C-Means with Automated Feature Selection for Seafloor Segmentation. Society for Optics and Photonics Defense + Commercial Sensing, Orlando, FL.
  9. J. Peeples, A. Zare, 2018. Synthetic Aperture SONAR Soft Segmentation using Possibilistic Fuzzy Local Information C-Means. University of Florida Water Institute Symposium, Gainesville, FL.

Poster Presentations

  1. J. Peeples, J. Jameson, N. Kotta, W. Stoppel, A. Zare, 2021. Spatial Histogram Layers in Convolutional Neural Network Models for Adipose Segmentation in Histological Silk Implant Images. Biomedical Engineering Society Annual Meeting, Orlando, FL.
  2. J. Peeples, 2021. Connecting the Past and Present: Histogram Layers for Texture Analysis, Notre Dame Future Faculty Workshop, South Bend, IL.
  3. J. Peeples, B. Driggers, G. Contreras, N. Tracht, S. Chen, M. Bedwell, 2017. Using the Engineering Force: BHAMSolo Senior Design Project. University of Alabama at Birmingham Spring Expo, Birmingham, AL. (Served as Team Lead for the project)
  4. J. Peeples, M. Al-Qizwini, H. Radha, 2017. LIVE ON: Lane, Sign, and Vehicle Detection in Various Environments,” Emerging Researchers National Conference in STEM, Washington, D.C. (Travel Award recipient)