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Artikel 6551 TOMATOD: EVALUATION OF OBJECT DETECTION ALGORITHMS ON A NEW REAL-WORLD TOMATO DATASET
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLIII-B3-2020, 2020: 1077-1084
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Artikel 6552 Tools and algorithms for the construction and analysis of systems: a special issue on tool papers for TACAS 2021
Enthalten in International journal on software tools for technology transfer Bd. 25, 17.2.2023, Nr. 2, date:4.2023: 129-131
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Artikel 6553 Topological and functional comparison of community detection algorithms in biological networks
Enthalten in BMC bioinformatics Bd. 20, 27.4.2019, Nr. 1, date:12.2019: 1-25
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Artikel 6554 Topological network features determine convergence rate of distributed average algorithms
Enthalten in Scientific reports Bd. 12, 17.12.2022, Nr. 1, date:12.2022: 1-21
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Artikel 6555 Toward coupling of nonlinear support vector regression and crowd intelligence optimization algorithms in estimation of suspended sediment load
Enthalten in Applied water science Bd. 14, 9.8.2024, Nr. 9, date:9.2024: 1-17
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Artikel 6556 Towards a decision support system for post bariatric hypoglycaemia: development of forecasting algorithms in unrestricted daily-life conditions
Enthalten in BMC medical informatics and decision making Bd. 25, 20.1.2025, Nr. 1, date:12.2025: 1-11
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Artikel 6557 Towards a standard benchmark for phenotype-driven variant and gene prioritisation algorithms: PhEval - Phenotypic inference Evaluation framework
Enthalten in BMC bioinformatics Bd. 26, 22.3.2025, Nr. 1, date:12.2025: 1-18
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Artikel 6558 Towards determining the presence of barren plateaus in some chemically inspired variational quantum algorithms
Enthalten in Communications Physics Bd. 7, 18.10.2024, Nr. 1, date:12.2024: 1-9
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Artikel 6559 Towards greener city logistics: an application of agile routing algorithms to optimize the distribution of micro-hubs in Barcelona
Enthalten in European transport research review Bd. 16, 23.8.2024, Nr. 1, date:12.2024: 1-22
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Artikel 6560 Towards provably efficient quantum algorithms for large-scale machine-learning models
Enthalten in Nature Communications Bd. 15, 10.1.2024, Nr. 1, date:12.2024: 1-6
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