Results 21 to 30 of about 59,289 (169)
EMAT: Enhanced Multi-Aspect Attention Transformer for Financial Time Series Forecasting
EntropyFinancial time series prediction remains a challenging task due to the inherent non-stationarity, noise, and complex temporal dependencies present in market data.
Yingjun Chen +3 more
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An End-to-End Air Writing Recognition Method Based on Transformer
IEEE Access, 2023 The air-writing recognition task entails the computer’s ability to directly recognize and interpret user input generated by finger movements in the air.
Xuhang Tan +4 more
doaj +1 more source
Journal of Marine Science and EngineeringAs the IMO and the EU strengthen carbon emission regulations, eco-friendly voyage planning is increasingly recognized by ship owners as one of the most important performance factors of the vessel fleet.
Juhyang Lee +4 more
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Checking Model Transformation Refinement [PDF]
, 2013 The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-38883-5_15 Proceedings of 6th International Conference, ICMT 2013, Budapest, Hungary, June 18-19, 2013 Refinement is a central notion in computer science, meaning that some artefact S can be safely replaced by a refinement R, which preserves S’s properties.
Büttner, Fabian +3 more
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The Specialist’s Paradox: Generalist AI May Better Organize Medical Knowledge
AlgorithmsThis study investigates the ability of six pre-trained sentence transformers to organize medical knowledge by performing unsupervised clustering on 70 high-level Medical Subject Headings (MeSH) terms across seven medical specialties.
Carlo Galli +3 more
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Transformer models in biomedicine [PDF]
BMC Medical Informatics and Decision MakingAbstractDeep neural networks (DNN) have fundamentally revolutionized the artificial intelligence (AI) field. The transformer model is a type of DNN that was originally used for the natural language processing tasks and has since gained more and more attention for processing various kinds of sequential data, including biological sequences and structured
Madan, Sumit +5 more
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Transformer-Based Vehicle-Trajectory Prediction at Urban Low-Speed T-Intersection
SensorsTransformer-based models have demonstrated outstanding performance in trajectory prediction; however, their complex architecture demands substantial computing power, and their performance degrades significantly in long-term prediction.
Jae Kwan Lee
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Variability Model Transformations: Towards Unifying Variability Modeling
2020 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 2020 A plethora of variability modeling approaches has been developed in the last 30 years. Feature modeling and decision modeling became the most common and well-known groups of variability modeling approaches. Even within these groups, however, there are many different variants of approaches.
Feichtinger, Kevin, Rabiser, Rick
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MANTra: Towards Model Transformation Testing [PDF]
2010 Seventh International Conference on the Quality of Information and Communications Technology, 2010 Model-driven development is gaining importance in software engineering practice. This increasing usage asks for a new generation of testing tools to verify correctness and suitability of model transformations. This paper presents a novel approach to unit testing QVT Operational (QVTO) transformations, which overcomes limitations of currently available ...
CIANCONE, ANDREA +2 more
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Playing Flappy Bird Based on Motion Recognition Using a Transformer Model and LIDAR Sensor
SensorsA transformer neural network is employed in the present study to predict Q-values in a simulated environment using reinforcement learning techniques.
Iveta Dirgová Luptáková +2 more
doaj +1 more source