Results 11 to 20 of about 8,974 (165)
Bearing Fault Diagnosis Based on Small Sample Learning of Maml–Triplet
Applied Sciences, 2022 Since the emergence of artificial intelligence and deep learning methods, the fault diagnosis of bearings in rotating machinery has gradually been realized, reducing the high costs of bearing faults.
Qiang Cheng +5 more
doaj +2 more sources
Dif-MAML: Decentralized Multi-Agent Meta-Learning [PDF]
IEEE Open Journal of Signal Processing, 2022 The objective of meta-learning is to exploit knowledge obtained from observed tasks to improve adaptation to unseen tasks. Meta-learners are able to generalize better when they are trained with a larger number of observed tasks and with a larger amount ...
Mert Kayaalp, Stefan Vlaski, Ali Sayed
doaj +5 more sources
Alpha MAML: Adaptive Model-Agnostic Meta-Learning
, 2019 Model-agnostic meta-learning (MAML) is a meta-learning technique to train a model on a multitude of learning tasks in a way that primes the model for few-shot learning of new tasks.
Baydin, Atılım Güneş +2 more
core +3 more sources
Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2 [PDF]
Geoscientific Model Development, 2023 In the Energy Exascale Earth System Model (E3SM) Multi-scale Modeling Framework (MMF), where parameterizations of convection and turbulence are replaced by a 2-D cloud-resolving model (CRM), there are multiple options to represent land–atmosphere ...
J. Lee, W. M. Hannah, D. C. Bader
doaj +1 more source
comparison of small sample methods for Handshape Recognition
Journal of Computer Science and Technology, 2023 Automatic Sign Language Translation (SLT) systems can be a great asset to improve the communication with and within deaf communities. Currently, the main issue preventing effective translation models lays in the low availability of labelled data, which ...
Franco Ronchetti +6 more
doaj +1 more source
Human Activity Recognition with Meta-learning and Attention [PDF]
Jisuanji kexue, 2023 With the in-depth research of deep learning technology,its application and development in the field of behavior recognition have been greatly promoted.Current research on behavior recognition based on deep learning usually requires a large training data ...
WANG Jiahao, ZHONG Xin, LI Wenxiong, ZHAO Dexin
doaj +1 more source
Permute-MAML: exploring industrial surface defect detection algorithms for few-shot learning
Complex & Intelligent Systems, 2023 Computer vision has developed rapidly in recent years, invigorating the area of industrial surface defect detection while also providing it with modern perception capabilities.
ShanChen Pang +4 more
doaj +1 more source
Fairness warnings and fair-MAML [PDF]
Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 2020 Motivated by concerns surrounding the fairness effects of sharing and transferring fair machine learning tools, we propose two algorithms: Fairness Warnings and Fair-MAML. The first is a model-agnostic algorithm that provides interpretable boundary conditions for when a fairly trained model may not behave fairly on similar but slightly different tasks ...
Slack, Dylan, '19 +2 more
openaire +2 more sources
IEEE Access, 2023 Indian languages share a lot of overlap in acoustic and linguistic content. Though different languages use different writing systems, the phoneme sets logically overlap.
C. S. Anoop, A. G. Ramakrishnan
doaj +1 more source
Identifying Site‐Level Data Integrity Risks in Alzheimer’s Trials via Subject‐Level Heuristics and a Novel Machine Learning Framework [PDF]
Alzheimers DementAbstract Background Undetected data integrity issues in Alzheimer’s disease (AD) trials often appear as “paradoxical” participant profiles with atypical or implausible profiles that can distort efficacy signals and threaten the validity of study conclusions.
Geraci J.
europepmc +2 more sources