Results 131 to 140 of about 13,513 (170)

Analysis of the impact of irradiance and temperature on photovoltaic production: A statistical and machine learning approach. [PDF]

MethodsX
Ndiaye EHM, Ndiaye A, Faye M, Gueye D, Ba A, Traore M.   +5 more
europepmc   +1 more source

Unsupervised Learning-Based Anomaly Detection for Bridge Structural Health Monitoring: Identifying Deviations from Normal Structural Behaviour. [PDF]

Sensors (Basel)
Nesackon Abraham J, Tran MQ, Jayaraj JS, Matos JC, Valluzzi MR, Dang SN.   +5 more
europepmc   +1 more source

MGM-AE: Self-Supervised Learning on 3D Shape Using Mesh Graph Masked Autoencoders

2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Yang, Zhangsihao, Ding, Kaize, Liu, Huan, Wang, Yalin   +3 more
openaire   +2 more sources

Multi-Output Prediction and Optimization of CO₂ Laser Cutting Quality in FFF-Printed ASA Thermoplastics Using Machine Learning Approaches. [PDF]

Polymers (Basel)
Der O.
europepmc   +1 more source

I3D-AE-LSTM: Combining action representations using a 2-stream autoencoder for Action Quality Assessment

Expert Systems with Applications
Tevin Moodley, Dustin van der Haar
openaire   +1 more source

AE-BPNN: autoencoder and backpropagation neural network-based model for lithium-ion battery state of health estimation. [PDF]

Sci Rep
Al-Dulaimi AA, Guneser MT, Al-Shabandar R, Gu Y, Syafrudin M, Fitriyani NL.   +5 more
europepmc   +1 more source

Attention-enhanced residual autoencoder for NIR spectral feature extraction and classification of grain varieties. [PDF]

Sci Rep
Kabiso AC, Ko CH.
europepmc   +1 more source

Study of anomaly registration detection based on multilayer kernel autoencoder extreme learning machine model. [PDF]

Sci Rep
Gu Z, Guo L, Huang J, Xiao D, Ke Y, Zhang Y.   +5 more
europepmc   +1 more source

AE-BoNet: A Deep Learning Method for Pediatric Bone Age Estimation using an Unsupervised Pre-Trained Model. [PDF]

J Biomed Phys Eng
Sirati-Amsheh M, Shabaninia E, Chaparian A.   +2 more
europepmc   +1 more source

Uncovering Structure-Conductivity Relationships in Anion Exchange Membranes (AEMs) Using Interpretable Machine Learning. [PDF]

Membranes (Basel)
Naghshnejad P, Das D, Romagnoli JA, Kumar R, Chen J.   +4 more
europepmc   +1 more source