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How low Should You Go? - Conceptualization of the Service Granularity Framework.

, , and . ECIS, page Research Paper 32. (2016)

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Real-timeservice profiling for the efficient simulation of logistics networks., , , , and . ICALT, page 253-258. IEEE, (2014)Towards Automated Logistics Service Comparison - Decision Support for Logistics Network Management., , , and . ICEIS (1), page 259-264. SciTePress, (2012)Comparison of deep learning methods for grapevine growth stage recognition., , , , , , and . Comput. Electron. Agric., (August 2023)Research in Progress: Implementation of an Integrated Data Model for an Improved Monitoring of Environmental Processes., , , , , , and . BIS (Workshops), volume 263 of Lecture Notes in Business Information Processing, page 332-339. Springer, (2016)Go with the Flow - Design of Cloud Logistics Service Blueprints., , and . HICSS, page 1-10. ScholarSpace / AIS Electronic Library (AISeL), (2017)An Architectural Blueprint for a Multi-purpose Anomaly Detection on Data Streams., , and . ICEIS (1), page 470-476. SciTePress, (2019)Adapting a Generic Smart Service Platform Architecture to the Road-Based Physical Internet., , , , and . ICEIS (1), page 749-756. SCITEPRESS, (2023)Towards Real-Time Data Acquisition for Simulation of Logistics Service Systems., , , and . ICCL, volume 8197 of Lecture Notes in Computer Science, page 242-256. Springer, (2013)Data modeling of smart urban object networks., , , and . WI, page 1104-1109. ACM, (2017)Deep learning for grape variety recognition., , , , , , and . KES, volume 176 of Procedia Computer Science, page 1211-1220. Elsevier, (2020)