| Collision-free autonomous robot navigation in unknown environments utilizing PSO for path planning E Krell, A Sheta, APR Balasubramanian, SA King Journal of Artificial Intelligence and Soft Computing Research 9 (4), 267-282, 2019 | 68 | 2019 |
| Autonomous Surface Vehicle energy-efficient and reward-based path planning using Particle Swarm Optimization and Visibility Graphs E Krell, SA King, LRG Carrillo Applied Ocean Research 122, 103125, 2022 | 28 | 2022 |
| Genetic identification of species responsible for depredation in commercial and recreational fisheries JM Drymon, PT Cooper, SP Powers, MM Miller, S Magnuson, E Krell, ... North American Journal of Fisheries Management 39 (3), 524-534, 2019 | 16 | 2019 |
| Importance of 3D convolution and physics on a deep learning coastal fog model H Kamangir, E Krell, W Collins, SA King, P Tissot Environmental Modelling & Software 154, 105424, 2022 | 9 | 2022 |
| Map generation and path planning for autonomous mobile robot in static environments using GA KU Gunasekaran, E Krell, A Sheta, SA King 2018 8th International Conference on Computer Science and Information …, 2018 | 4 | 2018 |
| Aggregation strategies to improve XAI for geoscience models that use correlated, high-dimensional rasters E Krell, H Kamangir, W Collins, SA King, P Tissot Environmental Data Science 2, e45, 2023 | 1 | 2023 |
| The influence of grouping features on explainable artificial intelligence for a complex fog prediction deep learning model E Krell, H Kamangir, J Friesand, J Judge, W Collins, SA King, P Tissot | 1 | 2022 |
| Game theoretic potential field for autonomous water surface vehicle navigation using weather forecasts E Krell, LRG Carrillo, SA King, JP Hespanha 2020 American Control Conference (ACC), 2112-2117, 2020 | 1 | 2020 |
| Autonomous Water Surface Vehicle Metaheuristic Mission Planning using Self-generated Goals and Environmental Forecasts E Krell, SA King, LRG Carrillo 2020 American Control Conference (ACC), 2502-2507, 2020 | 1 | 2020 |
| Using Grouped Features to Improve Explainable AI Results for Atmospheric AI Models that use Gridded Spatial Data and Complex Machine Learning Technique E Krell, P Tissot, A Mamalakis, W Collins, I Ebert-Uphoff, S King Authorea Preprints, 2024 | | 2024 |
| Interpretation and Attribution of Coastal Land Subsidence: An InSAR and Machine Learning Perspective X Qiao, T Chu, E Krell, P Tissot, S Holland, M Ahmed, D Smilovsky IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024 | | 2024 |
| A 10-year Metocean dataset for Laguna Madre, Texas, including for the Study of Extreme Cold Events MC White, M Vicens-Miquel, P Tissot, E Krell Data in Brief 52, 109828, 2024 | | 2024 |
| NWS Forecaster Perceptions of New AI Guidance for Coastal Fog Prediction CD Wirz, JL Demuth, M White, JT Radford, PE Tissot, MG Cains, ... 104th AMS Annual Meeting, 2024 | | 2024 |
| The Utility of Domain Knowledge When Developing Deep Learning Models to Predict Coastal Fog WG Collins, B Colburn, PE Tissot, SA King, E Krell, JK Williams 104th AMS Annual Meeting, 2024 | | 2024 |
| A Variational Autoencoder for Coastal Visibility Predictions: Architecture, Performance and R2X Potential B Colburn, P Tissot, JK Williams, SA King, WG Collins, E Krell, LC Gaudet, ... 104th AMS Annual Meeting, 2024 | | 2024 |
| Toward Prediction of Pyrocumulonimbus with Machine Learning CT Nguyen, EA Krell, J Nachamkin, DA Peterson, EJ Hyer, PE Tissot, ... 104th AMS Annual Meeting, 2024 | | 2024 |
| AI for Quality Control of Water Level Observations LR Abrams, J Spore, G Dusek, PE Tissot, E Krell, H Moustahfid 104th AMS Annual Meeting, 2024 | | 2024 |
| FogNet-V2: Multi-view Tensorized Transformer for Coastal Fog Forecasting E Krell, WG Collins, P Tissot, SA King, DJJ Gagne 104th AMS Annual Meeting, 2024 | | 2024 |
| Meteorological Interpretation of XAI Output Applied to a 3D Convolutional Neural Network Fog Prediction Model WG Collins, E Krell, PE Tissot, SA King 104th AMS Annual Meeting, 2024 | | 2024 |
| Exploring the Influence of Correlated Features on Geoscience AI Models to Improve the Scientific Insights Gained From Using Explainable AI Techniques for Feature Attribution E Krell, A Mamalakis, I Ebert-Uphoff, P Tissot, SA King AGU23, 2023 | | 2023 |
Scott A. KingProfessor, Department of Computing Sciences, Texas A&M University - Corpus ChristiVerified email at tamucc.edu
