| Applications of supervised machine learning in autism spectrum disorder research: a review KK Hyde, MN Novack, N LaHaye, C Parlett-Pelleriti, R Anden, DR Dixon, ... Review Journal of Autism and Developmental Disorders 6, 128-146, 2019 | 209 | 2019 |
| Learning in the machine: To share or not to share? J Ott, E Linstead, N LaHaye, P Baldi Neural Networks 126, 235-249, 2020 | 24 | 2020 |
| Multi-modal object tracking and image fusion with unsupervised deep learning N LaHaye, J Ott, MJ Garay, HM El-Askary, E Linstead IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2019 | 16 | 2019 |
| Assessing the vertical displacement of the grand Ethiopian renaissance dam during its filling using DInSAR technology and its potential acute consequences on the downstream … H El-Askary, A Fawzy, R Thomas, W Li, N LaHaye, E Linstead, T Piechota, ... Remote Sensing 13 (21), 4287, 2021 | 12 | 2021 |
| Applications of Supervised Machine Learning in Autism Spectrum Disorder Research: a Review. Rev J Autism Dev Disord 6, 128–146 (2019) K Hyde, MN Novack, N LaHaye | 5 | |
| A quantitative validation of multi-modal image fusion and segmentation for object detection and tracking N LaHaye, MJ Garay, BD Bue, H El-Askary, E Linstead Remote Sensing 13 (12), 2364, 2021 | 3 | 2021 |
| Scalable Hyperspectral Inversion with Uncertainty Quantification L Hopkins, N LaHaye, J Kravitz, S Mauceri AGU Fall Meeting Abstracts 2022, GC42D-0742, 2022 | 1 | 2022 |
| Validation of Machine Learning Algorithms for Hyperspectral Inversion of Common Water Quality Indicators J Kravitz, L Hopkins, N LaHaye, S Mauceri AGU Fall Meeting Abstracts 2022, GC33C-02, 2022 | 1 | 2022 |
| NASA's Prototype Spectral Water Inversion Processor and Emulator (SWIPE): Towards Global Coastal and Inland Water Quality and Algal Biodiversity Monitoring J Kravitz, L Robertson-Lain, S Mauceri, L Hopkins, N LaHaye, T Norman, ... AGU Fall Meeting Abstracts 2022, B22D-1469, 2022 | 1 | 2022 |
| Pushing the limits of aquatic remote sensing: Synthetic data and deep learning for fast inverse emulation of a coupled water-atmosphere radiative transfer model J Kravitz, LS Guild, L Lain, S Mauceri, N LaHaye, L Hopkins, IG Brosnan 2024 Ocean Sciences Meeting, 2024 | | 2024 |
| Securing Digital Twins for Earth Science Processes with Blockchains N LaHaye, M Kantarcioglu, H Lee, Y Gel AGU23, 2023 | | 2023 |
| 3D Cloud Tomography using Multi-View Imaging by MISR+ MODIS/Terra, and Beyond: A New Approach based on Machine Learning, Large-Eddy Simulation, and a Custom Algorithmic … AB Davis, L Forster, N LaHaye, S Mauceri, M Kurowski AGU Fall Meeting Abstracts 2023, A53A-08, 2023 | | 2023 |
| Towards Operational 3D Cloud Tomography: Leveraging Machine Learning and Multi-Angle Passive Imaging L Forster, N LaHaye, M Kurowski, S Mauceri, AB Davis AGU Fall Meeting Abstracts 2023, A53A-07, 2023 | | 2023 |
| Automatic Smoke Plume and Wildfire Instance Tracking Across Multi-Sensor Scenes N LaHaye, H Lee, M Garay, Z Guo, M Dixon, Y Chen, ... IEEE IGARSS 2023, 2023 | | 2023 |
| Sentinel-6 Hydrology Measurements Capability Demonstration JD Desjonqueres, N LaHaye, S Desai 2023 Ocean Surface Topography Science Team Meeting, 2023 | | 2023 |
| Toward Automated Multi-Sensor Wildfire and Smoke Plume Instance Tracking N LaHaye, Y Chen, H Lee, MJ Garay, OV Kalashnikova, M Parashar, ... AGU23, 2023 | | 2023 |
| Integration of Explainable AI (XAI) into SIT-FUSE for Improved Multi-Sensor Wildfire and Smoke Plume Segmentation N Leet, N LaHaye, J Baijnath-Rodino AGU23, 2023 | | 2023 |
| Using Machine Learning to Accelerate MCMC for the CARbon DAta-MOdel fraMework N LaHaye, S Mauceri, AA Bloom Fall Meeting 2022, 2022 | | 2022 |
| Opportunities and Challenges using Observations and Simulated Data for Machine-Learning-Based Retrievals of Water Quality N LaHaye, L Hopkins, J Kravitz, S Mauceri Fall Meeting 2022, 2022 | | 2022 |
| Identification of wildfires and smoke plumes using multi-sensor input and unsupervised and supervised machine learning for improved spatiotemporal coverage and facilitation of … N LaHaye, K Yun, H Lee, A Goodman, K Gorski, M Garay, O Kalashnikova AGU Fall Meeting Abstracts 2021, IN31A-09, 2021 | | 2021 |
Erik LinsteadAssociate Professor, Fowler School of Engineering, Chapman University在 chapman.edu 的电子邮件经过验证
