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Publication search results
found 20 matches
- 2023
- Mostafa Rastgou, Yong He, Jin Wang, Hossein Bayat, Meihong Shao, Yawei Li, Qianjing Jiang:
A technical evaluation on the mathematical attitudes and fitting accuracy of soil moisture retention curve models. Comput. Electron. Agric. 215: 108347 (2023) - Kapseok Chang, Keunyoung Kim, Sanguk Lee, Jae-Hean Kim, Junghoon Lee, Hyungju Kim, Young-Jo Ko, Ilgyu Kim, Seung Chan Bang:
Technical challenges and solutions for 10 cm-level positioning accuracy towards 6G. ICT Express 9(3): 492-506 (2023) - Sigit Anggraito, Rahman Parentio, Ratih Ruffianti, Baskoro Nugroho, Fifien Ervianti, Dian Hendrayana, Arief Hamdani Gunawan:
Blockchain-Based Data Management System for Validation and Accuracy of Technical Data in Broadband Networks. APCC 2023: 459-464 - Shubham Agrawal, Nitin Kumar, Geetanjali Rathee, Carlos T. Calafate, Chaker Abdelaziz Kerrache:
Determining the Accuracy of Reinforced Model via Sentiment and Technical Analysis as a Stock Market Prediction Technique. ICT-DM 2023: 1-4 - 2022
- Jan MacDonald:
The reliability of deep learning for signal and image processing: Interpretability, robustness, and accuracy. Technical University of Berlin, Germany, 2022 - 2021
- Pascal Van Hentenryck:
Technical perspective: Finding the sweet spot amid accuracy and performance. Commun. ACM 64(11): 120 (2021) - Oleksandr Turovsky, Valerii Kozlovskyi, Yuliia Boiko, Vitaliy Klobukov:
Substantiation of Information Technology on Improving the Accuracy of the Signal Synchronization Received by the Radio Technical System. IT&I Workshops 2021: 205-214 - 2020
- Maria Teresa Baldassarre, Valentina Lenarduzzi, Simone Romano, Nyyti Saarimäki:
On the diffuseness of technical debt items and accuracy of remediation time when using SonarQube. Inf. Softw. Technol. 128: 106377 (2020) - 2019
- Nyyti Saarimäki, Maria Teresa Baldassarre, Valentina Lenarduzzi, Simone Romano:
On the Accuracy of SonarQube Technical Debt Remediation Time. SEAA 2019: 317-324 - Gabriel Trujillo-Hernández, Julio C. Rodríguez-Quiñonez, Luis R. Ramírez-Hernández, Moises J. Castro-Toscano, Daniel Hernández-Balbuena, Wendy Flores-Fuentes, Oleg Sergiyenko, Lars Lindner, Paolo Mercorelli:
Accuracy Improvement by Artificial Neural Networks in Technical Vision System. IECON 2019: 5572-5577 - 2018
- Ursula Neumann:
Stability and Accuracy Analysis of a Feature Selection Ensemble for Binary Classification in Biomedical Datasets. Technical University Munich, Germany, 2018 - 2015
- Robert Brem:
Highly parallel ray based wave propagation modeling and improved accuracy concepts for radiation and scattering problems involving composite metallic and dielectric objects. Technical University Munich, Germany, Verlag Dr. Hut 2015, ISBN 978-3-8439-2335-4, pp. 1-167 - 2014
- Stefan Brandmaier:
Experimental design methods to increase the accuracy of in silico models (Methoden der statistischen Versuchsplanung zur Verbesserung der Qualität von in silico Modellen). Technical University of Munich, Germany, 2014 - Ahmed Noori Rashid:
Identification of RFID indoor system and influence of the propagation parameters on the localization accuracy. National Technical University of Athens, Greece, 2014 - 2012
- Sami Laine:
APC-SIMULATOR: Demonstrating the Effects of Technical and Semantic Errors in the Accuracy of Hospital Reporting. ICIQ 2012: 85-98 - 2011
- Peter Keitler:
Management of tracking: and tracking accuracy in industrial augmented reality environments. Technical University Munich, 2011, pp. 1-249 - Tapani Koivukangas, Jani P. A. Katisko, John P. Koivukangas:
Technical accuracy of an O-arm registered surgical navigator. EMBC 2011: 2148-2151 - 2008
- Asif Ullah Khan, T. K. Bandopadhyaya, Sudhir Kumar Sharma:
Comparisons of Stock Rates Prediction Accuracy Using Different Technical Indicators with Backpropagation Neural Network and Genetic Algorithm Based Backpropagation Neural Network. ICETET 2008: 575-580 - 2007
- Reiner Jedermann, Jean-Pierre Emond, Walter Lang:
Shelf Life Prediction by Intelligent RFID - Technical Limits of Model Accuracy. LDIC 2007: 231-238 - 2003
- Parag C. Pendharkar, James A. Rodger:
Technical efficiency-based selection of learning cases to improve forecasting accuracy of neural networks under monotonicity assumption. Decis. Support Syst. 36(1): 117-136 (2003)
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