Dr. rer. nat. Michael Schirrmann
Articles in peer reviewed journals [43 Results]
- Darvishi, A.; Yousefi, M.; Schirrmann, M.; Ewert, F. (2024): Exploring biodiversity patterns at the landscape scale by linking landscape energy and land use/land cover heterogeneity. Science of the Total Environment. : p. 170163. Online: https://doi.org/10.1016/j.scitotenv.2024.170163
- Alirezazadeh, P.; Schirrmann, M.; Stolzenburg, F. (2023): A comparative analysis of deep learning methods for weed classification of high-resolution UAV images. Journal of Plant Diseases and Protection. : p. 227-236. Online: https://doi.org/10.1007/s41348-023-00814-9
- Salamut, C.; Kohnert, I.; Landwehr, N.; Pflanz, M.; Schirrmann, M.; Zare, M. (2023): Deep Learning Object Detection for Image Analysis of Cherry Fruit Fly (Rhagoletis cerasi L.) on Yellow Sticky Traps. Gesunde Pflanzen. (1): p. 37-48. Online: https://doi.org/10.1007/s10343-022-00794-0
- Alirezazadeh, P.; Schirrmann, M.; Stolzenburg, F. (2023): Improving Deep Learning-based Plant Disease Classification with Attention Mechanism. Gesunde Pflanzen. (1): p. 49-59. Online: https://doi.org/10.1007/s10343-022-00796-y
- Tang, Z.; Wang, M.; Schirrmann, M.; Dammer, K.; Li, X.; Brueggeman, R.; Sankaran, S.; Carter, A.; Pumphrey, M.; Hu, Y.; Chen, X.; Zhang, Z. (2023): Affordable High Throughput Field Detection of Wheat Stripe Rust Using Deep Learning with Semi-Automated Image Labeling. Computers and Electronics in Agriculture. (April): p. 107709. Online: https://doi.org/10.1016/j.compag.2023.107709
- Li, M.; Shamshiri, R.; Weltzien, C.; Schirrmann, M. (2022): Crop Monitoring Using Sentinel-2 and UAV Multispectral Imagery: A Comparison Case Study in Northeastern Germany. Remote Sensing. (17): p. 4426. Online: https://doi.org/10.3390/rs14174426
- Li, M.; Shamshiri, R.; Schirrmann, M.; Weltzien, C.; Shafian, S.; Laursen, M. (2022): UAV Oblique Imagery with an Adaptive Micro-Terrain Model for Estimation of Leaf Area Index and Height of Maize Canopy from 3D Point Clouds. Remote Sensing. (2): p. 585. Online: https://doi.org/10.3390/rs14030585
- Dammer, K.; Garz, A.; Hobart, M.; Schirrmann, M. (2022): Combined UAV- and tractor-based stripe rust monitoring in winter wheat under field conditions. Agronomy Journal. (1): p. 651-661. Online: https://doi.org/10.1002/agj2.20916
- Dammer, K.; Schirrmann, M. (2022): Primarily tests of a optoelectronic in-canopy sensor for evaluation of vertical disease infection in cereals. Pest Management Science. (1): p. 143-149. Online: https://doi.org/10.1002/ps.6623
- Philips, H.; Bach, E.; Bartz, M.; Bennett, J.; Beugnon, R.; Briones, M.; Brown, G.; Ferlian, O.; Gongalsky, K.; Guerra, C.; König-Ries, B.; Krebs, J.; Orgiazzi, A.; Ramirez, K.; Russel, D.; Schwarz, B.; Wall, D.; Brose, U.; Decaëns, T.; Lavelle, P.; Loreau, M.; Mathieu, J.; Mulder, C.; van der Putten, W.; Rillig, M.; Thakur, M.; de Vries, F.; Wardle, D.; Ammer, C.; Ammer, S.; Arai, M.; Ayuke, F.; Baker, G.; Baretta, D.; Barkusky, D.; Beauséjour, R.; Bedano, J.; Birkhofer, K.; Blanchart, E.; Blossey, B.; Bolger, T.; Bradley, R.; Brossard, M.; Burtis, J.; Capowiez, Y.; Cavagnaro, T.; Choi, A.; Clause, J.; Cluzeau, D.; Coors, A.; Crotty, F.; Crumsey, J.; Dávalos, A.; Díaz Cosín, D.; Dobson, A.; Domínguez, A.; Duhor, A.; van Eekeren, N.; Emmerling, C.; Falco, L.; Fernández, R.; Fonte, S.; Fragoso, C.; Franco, A.; Fusilero, A.; Geraskina, A.; Gholami, S.; González, G.; Gundale, M.; Gutiérrez López, M.; Hackenberger, B.; Hackenberger, D.; Hernández, L.; Hirth, J.; Hishi, T.; Holdsworth, A.; Holmstrup, M.; Hopfensperger, K.; Huerta Lwanga, E.; Huhta, V.; Hurisso, T.; Iannine III, B.; Iordache, M.; Irmler, U.; Ivask, M.; Jesús, J.; Johnson-Maynard, J.; Joschko, M.; Kaneko, N.; Kanianska, R.; Keith, A.; Kernecker, M.; Koné, A.; Kooch, Y.; Kukkonen, S.; Lalthanzara, H.; Lammel, D.; Lebedev, I.; Le Cadre, E.; Lincoln, N.; López-Hernández, D.; Loss, S.; Marichal, R.; Matula, R.; Minamiya, Y.; Moos, J.; Moreno, G.; Morón-Ríos, A.; Motohiro, H.; Muys, B.; Neirynck, J.; Norgrove, L.; Novo, M.; Nuutinen, V.; Nuzzo, V.; Mujeeb Rahman, P.; Pansu, J.; Paudel, S.; Pérès, G.; Pérez-Camacho, L.; Ponge, J.; Pritzel, J.; Rapoport, I.; Rashid, M.; Rebollo, S.; Rodríguez, M.; Roth, A.; Rousseau, G.; Rozen, A.; Sayad, E.; van Schaik, L.; Scharenbroch, B.; Schirrmann, M.; Schmidt, O.; Schröder, B.; Seeber, J.; Shashkov, M.; Singh, J.; Smith, S.; Steinwandter, M.; Szlavecz, K.; Talavera, J.; Trigo, D.; Tsukamoto, J.; Uribe-López, S.; de Valença, A.; Virto, I.; Wackett, A.; Warren, M.; Webster, E.; Wehr, N.; Whalen, J.; Wironen, M.; Wolters, V.; Wu, P.; Zenkova, I.; Zhang, W.; Cameron, E.; Eisenhauer, N. (2021): Global data on earthworm abundance, biomass, diversity and corresponding environmental properties. Scientific Data. : p. 136. Online: https://doi.org/10.1038/s41597-021-00912-z