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 +6 more
wiley +1 more source
Recurrent Convolutional Network for Video-based Person Re-Identification
, 2016 In this paper we propose a novel recurrent neural networkarchitecture for video-based person re-identification.Given the video sequence of a person, features are extracted from each frame using a convolutional neural network that incorporates a recurrent
Martinez del Rincon, Jesus; id_orcid +5 more
core +1 more source
A convolutional recurrent neural network with attention for response prediction to repetitive transcranial magnetic stimulation in major depressive disorder. [PDF]
Sci Rep, 2023 Shahabi MS +3 more
europepmc +1 more source
Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges
Advanced Robotics Research, EarlyView.This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder +3 more
wiley +1 more source
Lipreading with convolutional and recurrent neural network models [PDF]
, 2017 Lip reading is the process of speech recognition from solely visual information. The goal of this thesis is to perform a silence vs. speech classification, and to recognize the triphone spoken by a talking head, given only the video using neural network ...
Zhu, Tianyilin
core
Comparing recurrent and convolutional neural networks for predicting wave propagation [PDF]
, 2020 Dynamical systems can be modelled by partial differential equations and numerical computations are used everywhere in science and engineering. In this work, we investigate the performance of recurrent and convolutional deep neural network architectures ...
Pignatelli, Eduardo +5 more
core
Research on a Bearing Fault Diagnosis Method Based on a CNN-LSTM-GRU Model
MachinesIn view of the problem of the insufficient performance of deep learning models in time series prediction and poor comprehensive space–time feature extraction, this paper proposes a diagnostic method (CNN-LSTM-GRU) that integrates convolutional neural ...
Kaixu Han, Wenhao Wang, Jun Guo
doaj +1 more source
GCRNN: graph convolutional recurrent neural network for compound-protein interaction prediction. [PDF]
BMC Bioinformatics, 2022 Elbasani E +5 more
europepmc +1 more source
Solid Harmonic Wavelet Bispectrum for Image Analysis
Advanced Science, EarlyView.The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown +3 more
wiley +1 more source
Convolutional Recurrent Neural Network for Dynamic Functional MRI Analysis and Brain Disease Identification. [PDF]
Front Neurosci, 2022 Lin K +5 more
europepmc +1 more source