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pro vyhledávání: '"Roscher, A A"'
Crop yield forecasting plays a significant role in addressing growing concerns about food security and guiding decision-making for policymakers and farmers. When deep learning is employed, understanding the learning and decision-making processes of t
Externí odkaz:
http://arxiv.org/abs/2407.08274
Autor:
Sinhamahapatra, Poulami, Schwaiger, Franziska, Bose, Shirsha, Wang, Huiyu, Roscher, Karsten, Guennemann, Stephan
Detecting and localising unknown or Out-of-distribution (OOD) objects in any scene can be a challenging task in vision. Particularly, in safety-critical cases involving autonomous systems like automated vehicles or trains. Supervised anomaly segmenta
Externí odkaz:
http://arxiv.org/abs/2404.07664
Publikováno v:
Proceedings of the AAAI-make Spring Symposium, 2024
Generative AI is increasingly important in software engineering, including safety engineering, where its use ensures that software does not cause harm to people. This also leads to high quality requirements for generative AI. Therefore, the simplisti
Externí odkaz:
http://arxiv.org/abs/2404.15317
Autor:
Sinhamahapatra, Poulami, Shit, Suprosanna, Sekuboyina, Anjany, Husseini, Malek, Schinz, David, Lenhart, Nicolas, Menze, Joern, Kirschke, Jan, Roscher, Karsten, Guennemann, Stephan
Publikováno v:
Machine.Learning.for.Biomedical.Imaging. 2 (2024)
Vertebral fracture grading classifies the severity of vertebral fractures, which is a challenging task in medical imaging and has recently attracted Deep Learning (DL) models. Only a few works attempted to make such models human-interpretable despite
Externí odkaz:
http://arxiv.org/abs/2404.02830
Autor:
Roscher, Ribana, Rußwurm, Marc, Gevaert, Caroline, Kampffmeyer, Michael, Santos, Jefersson A. dos, Vakalopoulou, Maria, Hänsch, Ronny, Hansen, Stine, Nogueira, Keiller, Prexl, Jonathan, Tuia, Devis
Recent developments and research in modern machine learning have led to substantial improvements in the geospatial field. Although numerous deep learning architectures and models have been proposed, the majority of them have been solely developed on
Externí odkaz:
http://arxiv.org/abs/2312.05327
Autor:
Drees, Lukas, Demie, Dereje T., Paul, Madhuri R., Leonhardt, Johannes, Seidel, Sabine J., Döring, Thomas F., Roscher, Ribana
Image-based crop growth modeling can substantially contribute to precision agriculture by revealing spatial crop development over time, which allows an early and location-specific estimation of relevant future plant traits, such as leaf area or bioma
Externí odkaz:
http://arxiv.org/abs/2312.03443
In response to the increasing global demand for food, feed, fiber, and fuel, digital agriculture is rapidly evolving to meet these demands while reducing environmental impact. This evolution involves incorporating data science, machine learning, sens
Externí odkaz:
http://arxiv.org/abs/2312.03437
Publikováno v:
IEEE Geoscience and Remote Sensing Letters, 2024
Protected natural areas are regions that have been minimally affected by human activities such as urbanization, agriculture, and other human interventions. To better understand and map the naturalness of these areas, machine learning models can be us
Externí odkaz:
http://arxiv.org/abs/2311.08936
Natural protected areas are vital for biodiversity, climate change mitigation, and supporting ecological processes. Despite their significance, comprehensive mapping is hindered by a lack of understanding of their characteristics and a missing land c
Externí odkaz:
http://arxiv.org/abs/2311.08923
The ability to detect learned objects regardless of their appearance is crucial for autonomous systems in real-world applications. Especially for detecting humans, which is often a fundamental task in safety-critical applications, it is vital to prev
Externí odkaz:
http://arxiv.org/abs/2307.04533