Results 101 to 110 of about 34,789 (293)

Research on a Bearing Fault Diagnosis Method Based on a CNN-LSTM-GRU Model

Machines
In 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

Speech emotion recognition based on improved masking EMD and convolutional recurrent neural network. [PDF]

Front Psychol, 2022
Sun C, Li H, Ma L.
europepmc   +1 more source

A Review on Sensor Technologies, Control Approaches, and Emerging Challenges in Soft Robotics

Advanced Robotics Research, EarlyView.
This review provides an introspective of sensors and controllers in soft robotics. Initially describing the current sensing methods, then moving on to the control methods utilized, and finally ending with challenges and future directions in soft robotics focusing on the material innovations, sensor fusion, and embedded intelligence for sensors and ...
Ean Lovett, Maxwell Hammond, Niloufar Seyfi, Amirreza Fahim Golestaneh, Venanzio Cichella, Caterina Lamuta   +5 more
wiley   +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, Shalbaf A, Rostami R, Kazemi R.   +3 more
europepmc   +1 more source

Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation [PDF]

, 2016
Jianxu Chen, Lin Yang, Yizhe Zhang, Mark Alber, Danny Z. Chen   +4 more
openalex   +1 more source

Recurrent Convolutional Neural Networks for Scene Parsing

, 2013
Scene parsing is a technique that consist on giving a label to all pixels in an image according to the class they belong to. To ensure a good visual coherence and a high class accuracy, it is essential for a scene parser to capture image long range dependencies.
Pinheiro, Pedro H. O., Collobert, Ronan
openaire   +2 more sources

Improving the Robustness of Visual Teach‐and‐Repeat Navigation Using Drift Error Correction and Event‐Based Vision for Low‐Light Environments

Advanced Robotics Research, EarlyView.
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley   +1 more source

Neural network device for recognizing speech commands based on hardware accelerators of the NEUROMATRIX family

Безопасность информационных технологий
Various approaches to solving the problem of speech command recognition in real time using artificial neural networks (ANN) of several types are considered.
Vladislav V. Zholondkovskiy, Yuri I. Bocharov, Vladimir A. Butuzov   +2 more
doaj   +1 more source

GCRNN: graph convolutional recurrent neural network for compound-protein interaction prediction. [PDF]

BMC Bioinformatics, 2022
Elbasani E, Njimbouom SN, Oh TJ, Kim EH, Lee H, Kim JD.   +5 more
europepmc   +1 more source

Convolutional unitary or orthogonal recurrent neural networks

, 2023
Recurrent neural networks are extremely powerful yet hard to train. One of their issues is the vanishing gradient problem, whereby propagation of training signals may be exponentially attenuated, freezing training. Use of orthogonal or unitary matrices, whose powers neither explode nor decay, has been proposed to mitigate this issue, but their ...
openaire   +2 more sources