Results 71 to 80 of about 30,442 (292)

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

Advanced Materials Technologies, EarlyView.
The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz, Yaroslav Mudryk, Jun Cui, Lucas Griffith, Duane D. Johnson, Julie Slaughter   +5 more
wiley   +1 more source

Deep Learning Autoencoders for Fast Fourier Transform-Based Clustering and Temporal Damage Evolution in Acoustic Emission Data from Composite Materials

Infrastructures
Structural health monitoring (SHM) in fiber-reinforced polymer (FRP) composites is essential to ensure safety and reliability during service, particularly in critical industries such as aerospace and wind energy. Traditional methods of analyzing Acoustic
Serafeim Moustakidis, Konstantinos Stergiou, Matthew Gee, Sanaz Roshanmanesh, Farzad Hayati, Patrik Karlsson, Mayorkinos Papaelias   +6 more
doaj   +1 more source

Directional Latent Hybridization: Beyond Random Noise in Physics‐Informed Generative Inverse Design of Nonlinear Metamaterials

Advanced Materials Technologies, EarlyView.
A physics‐informed generative framework introduces Directional Latent Hybridization (DLH) for the deterministic inverse design of nonlinear metamaterials. By hybridizing dominant traits from parent geometries in the latent space, DLH overcomes the instabilities of stochastic models to ensure high structural precision at high densities.
Semin Ahn, Jun Young Choi, Sung‐Hoon Ahn   +2 more
wiley   +1 more source

Stacked Sparse Autoencoders for EMG-Based Classification of Hand Motions: A Comparative Multi Day Analyses between Surface and Intramuscular EMG

Applied Sciences, 2018
Advances in myoelectric interfaces have increased the use of wearable prosthetics including robotic arms. Although promising results have been achieved with pattern recognition-based control schemes, control robustness requires improvement to increase ...
Muhammad Zia ur Rehman, Syed Omer Gilani, Asim Waris, Imran Khan Niazi, Gregory Slabaugh, Dario Farina, Ernest Nlandu Kamavuako   +6 more
doaj   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Generalization of iterative sampling in autoencoders

, 2020
International audienceGenerative autoencoders are designed to model a target distribution with the aim of generating samples and it has also been shown that specific non-generative autoencoders (i.e.
Cohendet, Romain, S. Rousset, M. Solinas, Mermillod, Martial, Reyboz, Marina, Galiez, Clovis, Rousset, Stéphane, C. Galiez, Solinas, Miguel, R. Cohendet, M. Reyboz, M. Mermillod   +11 more
core   +1 more source

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

Toroidal AutoEncoder

CoRR, 2019
Enforcing distributions of latent variables in neural networks is an active subject. It is vital in all kinds of generative models, where we want to be able to interpolate between points in the latent space, or sample from it. Modern generative AutoEncoders (AE) like WAE, SWAE, CWAE add a regularizer to the standard (deterministic) AE, which allows to ...
Maciej Mikulski, Jaroslaw Duda 0001
openaire   +3 more sources

TacVerse: A Multisensor Dataset and Benchmark for Cross‐Sensor Vision‐Based Tactile Perception

Advanced Robotics Research, EarlyView.
TacVerse provides a controlled benchmark of 106 800 tactile images from seven vision‐based tactile sensors across shape classification, grating classification, and force regression. Direct cross‐sensor transfer reveals substantial sensor‐shift degradation, with grating and force perception more affected than shape recognition.
Lan Wei, Gurmeher Khurana, Sirine Bhouri, Wenhao Hong, Zeyuan Xin, Qingzheng Cong, Wen Fan, Yanzheng Xiang, Dandan Zhang   +8 more
wiley   +1 more source

Linear autoencoders and nonlinear autoencoders (ReLU)

, 2020
Este trabalho é dedicado ao estudo de autoencoders lineares, onde se destacam as suas ligações com a técnica PCA e com autoencoders não lineares, nomeadamente, usando a função de ativação ReLU.
Teixeira, Rui Pedro Silva
core   +1 more source