| Graph weeds net: A graph-based deep learning method for weed recognition K Hu, G Coleman, S Zeng, Z Wang, M Walsh Computers and electronics in agriculture 174, 105520, 2020 | 97 | 2020 |
| Using energy requirements to compare the suitability of alternative methods for broadcast and site-specific weed control GRY Coleman, A Stead, MP Rigter, Z Xu, D Johnson, GM Brooker, ... Weed Technology 33 (4), 633-650, 2019 | 67 | 2019 |
| Deep learning techniques for in-crop weed recognition in large-scale grain production systems: a review K Hu, Z Wang, G Coleman, A Bender, T Yao, S Zeng, D Song, ... Precision Agriculture 25 (1), 1-29, 2024 | 36 | 2024 |
| Weed detection to weed recognition: reviewing 50 years of research to identify constraints and opportunities for large-scale cropping systems GRY Coleman, A Bender, K Hu, SM Sharpe, AW Schumann, Z Wang, ... Weed Technology 36 (6), 741-757, 2022 | 23 | 2022 |
| OpenWeedLocator (OWL): An open-source, low-cost device for fallow weed detection. G Coleman, W Salter, M Walsh Scientific Reports 12, 170, 2022 | 20 | 2022 |
| Low Energy Laser Treatments Control Annual Ryegrass (Lolium rigidum) G Coleman, C Betters, C Squires, S Leon-Saval, M Walsh Frontiers in Agronomy 2, 601542, 2021 | 20 | 2021 |
| Increasing the value and efficiency of herbicide resistance surveys CC Squires, GRY Coleman, JC Broster, C Preston, P Boutsalis, MJ Owen, ... Pest Management Science 77 (9), 3881-3889, 2021 | 14 | 2021 |
| Tillage based, site-specific weed control for conservation cropping systems MJ Walsh, CC Squires, GRY Coleman, MJ Widderick, AB McKiernan, ... Weed Technology 34 (5), 704-710, 2020 | 13 | 2020 |
| More eyes on the prize: open-source data, software and hardware for advancing plant science through collaboration GRY Coleman, WT Salter AoB Plants 15 (2), plad010, 2023 | 3 | 2023 |
| Multi-growth stage plant recognition: A case study of Palmer amaranth (Amaranthus palmeri) in cotton (Gossypium hirsutum) GRY Coleman, M Kutugata, MJ Walsh, MV Bagavathiannan Computers and Electronics in Agriculture 217, 108622, 2024 | 2 | 2024 |
| Investigating image-based fallow weed detection performance on Raphanus sativus and Avena sativa at speeds up to 30 km/h GRY Coleman, A Macintyre, MJ Walsh, WT Salter Computers and Electronics in Agriculture 215, 108419, 2023 | 2 | 2023 |
| Image‐based weed recognition and control: Can it select for crop mimicry? GRY Coleman, A Bender, MJ Walsh, P Neve Weed Research 63 (2), 77-82, 2023 | 1 | 2023 |
| Opportunities and constraints for image-based weed recognition in large-scale production systems G Coleman | | 2024 |
| Using Deep Learning for Recognition of Multi-Growth Stage Palmer Amaranth (Amaranthus palmeri) in Cotton (Gossypium hirsutum) Under Field Conditions G Coleman, M Bagavathiannan, M Walsh ASA, CSSA, SSSA International Annual Meeting, 2021 | | 2021 |
| Lasers, machine learning, weed recognition and new innovations in weed management G Coleman, C Squires, M Walsh GRAINS RESEARCH UPDATE, 58, 2020 | | 2020 |
| Using energy requirements to compare the suitability of alternative methods for broadcast and site-specific weed control–CORRIGENDUM GRY Coleman, A Stead, MP Rigter, Z Xu, D Johnson, GM Brooker, ... Weed Technology 34 (1), 153-154, 2020 | | 2020 |
| General plenary session–Day 2 Lasers, machine learning, weed recognition and new innovations in weed management G Coleman, C Squires, M Walsh GRAINS RESEARCH UPDATE, 174, 2020 | | 2020 |
| Advances in weed recognition: the importance of identifying the appropriate approaches for the development of a weed recognition algorithm for Australian cropping M Walsh, A Bender, G Coleman | | |
| Site-specific physical weed control M Walsh, G Coleman GRAINS RESEARCH UPDATE, 21, 0 | | |
Michael WalshProfessor, Charles Sturt University在 sydney.edu.au 的电子邮件经过验证
