| A novel attention-based LSTM cell post-processor coupled with bayesian optimization for streamflow prediction B Alizadeh, AG Bafti, H Kamangir, Y Zhang, DB Wright, KJ Franz Journal of Hydrology 601, 126526, 2021 | 99 | 2021 |
| Review and evaluation of deep learning architectures for efficient land cover mapping with UAS hyper-spatial imagery: A case study over a wetland M Pashaei, H Kamangir, MJ Starek, P Tissot Remote Sensing 12 (6), 959, 2020 | 94 | 2020 |
| FogNet: A multiscale 3D CNN with double-branch dense block and attention mechanism for fog prediction H Kamangir, W Collins, P Tissot, SA King, HTH Dinh, N Durham, J Rizzo Machine Learning with Applications 5, 100038, 2021 | 27 | 2021 |
| Deep learning-based single image super-resolution: an investigation for dense scene reconstruction with UAS photogrammetry M Pashaei, MJ Starek, H Kamangir, J Berryhill Remote Sensing 12 (11), 1757, 2020 | 27 | 2020 |
| A deep‐learning model to predict thunderstorms within 400 km2 South Texas domains H Kamangir, W Collins, P Tissot, SA King Meteorological Applications 27 (10.1002/met), 2020 | 27 | 2020 |
| Deep hybrid wavelet network for ice boundary detection in radra imagery H Kamangir, M Rahnemoonfar, D Dobbs, J Paden, G Fox IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018 | 22 | 2018 |
| Automatic centerline extraction of coverd roads by surrounding objects from high resolution satellite images H Kamangir, M Momeni, M Satari The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2017 | 14 | 2017 |
| 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 |
| Comparison of machine learning methods for leaf nitrogen estimation in corn using multispectral UAV images R Barzin, H Kamangir, GC Bora Transactions of the ASABE 64 (6), 2089-2101, 2021 | 7 | 2021 |
| Simultaneously Predicting Multiple Plant Traits from Multiple Sensors via Deformable CNN Regression P Raja, A Olenskyj, H Kamangir, M Earles arXiv preprint arXiv:2112.03205, 2021 | 5 | 2021 |
| A deep learning approach to urban street functionality prediction based on centrality measures and stacked denoising autoencoder F Noori, H Kamangir, S A. King, A Sheta, M Pashaei, ... ISPRS International Journal of Geo-Information 9 (7), 456, 2020 | 5 | 2020 |
| Effects of extreme floods on fluvial changes: the Khorramabad River as case study (western Iran) S Sharafi, H Kamangir, SA King, R Safaierad Arabian Journal of Geosciences 14 (12), 1140, 2021 | 4 | 2021 |
| Detecting ice layers in Radar images with deep hybrid networks H Kamangir, M Rahnemoonfar, D Dobbs, J Paden, GC Fox Proceedings of the IEEE Conference on Geoscience and Remote Sensing (IGARSS …, 2018 | 4 | 2018 |
| A deep learning based method to delineate the wet/dry shoreline and compute its elevation using high-resolution UAS imagery M Vicens-Miquel, FA Medrano, PE Tissot, H Kamangir, MJ Starek, ... Remote Sensing 14 (23), 5990, 2022 | 2 | 2022 |
| Evaluation and calibration of low‐cost off‐the‐shelf particulate matter sensors using machine learning techniques M Ghamari, H Kamangir, K Arezoo, K Alipour IET Wireless Sensor Systems 12 (5-6), 134-148, 2022 | 2 | 2022 |
| Large-scale spatio-temporal yield estimation via deep learning using satellite and management data fusion in vineyards H Kamangir, BS Sams, N Dokoozlian, L Sanchez, JM Earles Computers and Electronics in Agriculture 216, 108439, 2024 | 1 | 2024 |
| 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 |
| Deep Learning Automatic Detection of the Wet/Dry Shoreline at Fish Pass, Texas M Vicens-Miquel, FA Medrano, P Tissot, H Kamangir, M Starek IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium …, 2022 | 1 | 2022 |
| 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 |
| 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 |
Philippe TissotConrad Blucher Institute, Texas A&M University-Corpus ChristiVerified email at tamucc.edu
