Results 71 to 80 of about 1,166,366 (314)
Enhancing reinforcement learning controllers with GAN-generated data and transfer learning
SICE Journal of Control, Measurement, and System IntegrationThis study addresses the challenge of data scarcity in training reinforcement learning (RL) controllers for power system economic dispatch problems (EDP) by integrating Generative Adversarial Network (GAN)-generated synthetic data and transfer learning ...
Chang Xu +2 more
doaj +1 more source
Metrics for Evaluating Synthetic Time-Series Data of Battery
Applied SciencesThe advancements in artificial intelligence have encouraged the application of deep learning in various fields. However, the accuracy of deep learning algorithms is influenced by the quality of the dataset used.
Sujin Seol +3 more
doaj +1 more source
Attributed Network Embedding for Learning in a Dynamic Environment
, 2018 Network embedding leverages the node proximity manifested to learn a low-dimensional node vector representation for each node in the network. The learned embeddings could advance various learning tasks such as node classification, network clustering, and
Chang, Yi +5 more
core +1 more source
A Systematic Comparison of Alpha‐Synuclein Seed Amplification Assays for Increasing Reproducibility
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Seed amplification assays (SAAs) enable ultrasensitive detection of misfolded α‐synuclein across biofluids and tissues. Yet, heterogeneity in protocols limits cross‐study comparability and clinical translation. Here, we review α‐synuclein SAA methods and their performance across various biological matrices.
Manuela Amaral‐do‐Nascimento +3 more
wiley +1 more source
RULE-BASED HYBRID INTELLIGENT LEARNING ENVIRONMENT IMPLEMENTATION
Современные информационные технологии и IT-образование, 2018 Learning is considered as an intelligent process the development scenario of which, with an individual approach to the learner, is not known in advance.
Pavel D. Basalin +5 more
doaj +1 more source
Effectiveness of synthetic data generation for capsule endoscopy images
Medicine Science, 2021 With advances in digital healthcare technologies, optional therapeutic modules and tasks such as depth estimation, visual localization, active control, automatic navigation, and targeted drug delivery are desirable for the next generation of capsule ...
Mehmet Turan
doaj +1 more source
Arthritis Care &Research, EarlyView.Objective The purpose was to evaluate a biomarker score consisting of MUC5B rs35705950 promoter variant, plasma matrix metalloproteinase‐7 (MMP‐7), and serum anti–malondialdehyde‐acetaldehyde (anti‐MAA) antibody for rheumatoid arthritis (RA)–associated interstitial lung disease (ILD) risk stratification.
Kelsey Coziahr +16 more
wiley +1 more source
Sensors, 2021 Limited training data is one of the biggest challenges in the industrial application of deep learning. Generating synthetic training images is a promising solution in computer vision; however, minimizing the domain gap between synthetic and real-world ...
Leon Eversberg, Jens Lambrecht
doaj +1 more source
, 2020 This study proposes a deep neural network- (DNN-) based prediction model for creating synthetic log. Unlike previous studies, it focuses on building a reliable prediction model based on two criteria: fit-for-purpose of a target field (the Golden field in
Sungil Kim +4 more
semanticscholar +1 more source
What Do Large Language Models Know About Materials?
Advanced Engineering Materials, EarlyView.If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source