| Deep plant phenomics: a deep learning platform for complex plant phenotyping tasks JR Ubbens, I Stavness Frontiers in plant science 8, 1190, 2017 | 338 | 2017 |
| The use of plant models in deep learning: an application to leaf counting in rosette plants J Ubbens, M Cieslak, P Prusinkiewicz, I Stavness Plant methods 14, 1-10, 2018 | 278 | 2018 |
| Latent space phenotyping: automatic image-based phenotyping for treatment studies J Ubbens, M Cieslak, P Prusinkiewicz, I Parkin, J Ebersbach, I Stavness Plant Phenomics, 2020 | 44 | 2020 |
| Unsupervised domain adaptation for plant organ counting TW Ayalew, JR Ubbens, I Stavness Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020 | 37 | 2020 |
| A randomized controlled trial of attention modification for social anxiety disorder RN Carleton, MJNT Sapach, C Oriet, S Duranceau, LM Lix, ... Journal of anxiety disorders 33, 35-44, 2015 | 30 | 2015 |
| Corrigendum: deep plant phenomics: a deep learning platform for complex plant phenotyping tasks JR Ubbens, I Stavness Frontiers in plant science 8, 2245, 2018 | 23 | 2018 |
| Simulated plant images improve maize leaf counting accuracy C Miao, TP Hoban, A Pages, Z Xu, E Rodene, J Ubbens, I Stavness, ... BioRxiv, 706994, 2019 | 20 | 2019 |
| Deep neural networks for genomic prediction do not estimate marker effects J Ubbens, I Parkin, C Eynck, I Stavness, AG Sharpe The Plant Genome 14 (3), e20147, 2021 | 16 | 2021 |
| Autocount: Unsupervised segmentation and counting of organs in field images JR Ubbens, TW Ayalew, S Shirtliffe, A Josuttes, C Pozniak, I Stavness Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020 | 15 | 2020 |
| Images carried before the fire: The power, promise, and responsibility of latent phenotyping in plants MJ Feldmann, JL Gage, SD Turner‐Hissong, JR Ubbens The Plant Phenome Journal 4 (1), e20023, 2021 | 12 | 2021 |
| ProTractor: a lightweight ground imaging and analysis system for early-season field phenotyping N Higgs, B Leyeza, J Ubbens, J Kocur, W van der Kamp, T Cory, C Eynck, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 12 | 2019 |
| Darts: Double attention reference-based transformer for super-resolution M Aslahishahri, J Ubbens, I Stavness arXiv preprint arXiv:2307.08837, 2023 | 3 | 2023 |
| Quantitative evaluation of nonlinear methods for population structure visualization and inference J Ubbens, MJ Feldmann, I Stavness, AG Sharpe G3 12 (9), jkac191, 2022 | 1 | 2022 |
| Information Rate for Fast Time-Domain Instrument Classification J Ubbens, D Gerhard Music, Mind, and Embodiment: 11th International Symposium, CMMR 2015 …, 2016 | 1 | 2016 |
| HiTSR: A Hierarchical Transformer for Reference-based Super-Resolution M Aslahishahri, J Ubbens, I Stavness arXiv preprint arXiv:2408.16959, 2024 | | 2024 |
| GPFN: Prior-Data Fitted Networks for Genomic Prediction J Ubbens, I Stavness, AG Sharpe bioRxiv, 2023.09. 20.558648, 2023 | | 2023 |
| A Latent Variable Model for Plant Stress Phenotyping Using Deep Learning JR Ubbens University of Saskatchewan, 2020 | | 2020 |
| Sparse Coding Tone-Like Structures in Sound Using Local Image Features JR Ubbens The University of Regina (Canada), 2015 | | 2015 |
| Supporting Information: The use of plant models in deep learning: an application to leaf counting in rosette plants J Ubbens, M Cieslak, P Prusinkiewicz, I Stavness interpretation 57, 58, 0 | | |
