Results 81 to 90 of about 8,068,470 (297)
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Advanced Engineering Materials, EarlyView.Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source
Active learning for deep object detection by fully exploiting unlabeled data
Connection Science, 2023 Object detection is a challenging task that requires a large amount of labeled data to train high-performance models. However, labeling huge amounts of data is expensive, making it difficult to train a good detector with limited labeled data.
Feixiang Tan, Guansheng Zheng
doaj +1 more source
CLASSIFICATION BASED ON SEMI-SUPERVISED LEARNING: A REVIEW
Iraqi Journal for Computers and Informatics, 2021 Semi-supervised learning is the class of machine learning that deals with the use of supervised and unsupervised learning to implement the learning process. Conceptually placed between labelled and unlabeled data.
Aska Ezadeen Mehyadin +1 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
Semi-HFL: semi-supervised federated learning for heterogeneous devices
Complex & Intelligent Systems, 2022 In the vanilla federated learning (FL) framework, the central server distributes a globally unified model to each client and uses labeled samples for training.
Zhengyi Zhong +5 more
doaj +1 more source
Semi-supervised transductive speaker identification [PDF]
, 2009 We present an application of transductive semi-supervised learning to the problem of speaker identification. Formulating this problem as one of transduction is the most natural choice in some scenarios, such as when annotating archived speech data ...
Täckström, Oscar
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Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying
Advanced Engineering Materials, EarlyView.An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara +8 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source
A Local-to-Global Metric Learning Framework From the Geometric Insight
IEEE Access, 2020 Metric plays a key role in the description of similarity between samples. An appropriate metric for data can well represent their distribution and further promote the performance of learning tasks.
Yaxin Peng +3 more
doaj +1 more source
A Framework for Context-Aware Semi Supervised Learning [PDF]
, 2014 Supervised learning techniques require large number of labeled examples to build a classifier which is often difficult and expensive to collect. Unsupervised learning techniques, even though do not require labeled examples often form clusters regardless
Vijaya Geeta Dharmavaram, Shashi Mogalla
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