Results 51 to 60 of about 1,913 (199)

Multi-Scale Convolutional Recurrent Neural Network for Bearing Fault Detection in Noisy Manufacturing Environments

Applied Sciences, 2021
The failure of a facility to produce a product can have significant impacts on the quality of the product. Most equipment failures occur in rotating equipment, with bearing damage being the biggest cause of failure in rotating equipment.
Seokju Oh, Seugmin Han, Jongpil Jeong
doaj   +1 more source

A parametrically‐Conditioned Deep Learning Surrogate for Coherent Spinodal Decomposition

Advanced Theory and Simulations, Volume 9, Issue 2, February 2026.
Spinodal decomposition of strained alloys with cubic anisotropy is reproduced by a Convolutional Recurrent Neural Network, taking the misfit parameter as explicit input to return different morphologies. The predicted composition fields match phase‐field simulations over a broad range of parameters, allowing to reconstruct the full phase diagram.
Andrea Fantasia, Daniele Lanzoni, Niccolò Di Eugenio, Angelo Monteleone, Roberto Bergamaschini, Francesco Montalenti   +5 more
wiley   +1 more source

Performance Analysis of 3D Video Transmission Over Deep-Learning-Based Multi-Coded N-ary Orbital Angular Momentum FSO System

IEEE Access, 2021
Orbital angular momentum-shift keying (OAM-SK), which is the rapid switching of OAM modes, is vital but seriously impeded by the deficiency of OAM demodulation techniques, particularly when videos are transmitted over the system.
Shimaa A. El-Meadawy, Hossam M. H. Shalaby, Nabil A. Ismail, Ahmed E. A. Farghal, Fathi E. Abd El-Samie, Mohammed Abd-Elnaby, Walid El-Shafai   +6 more
doaj   +1 more source

Speaker Identification in Different Emotional States in Arabic and English

IEEE Access, 2020
Speaker recognition is an important application of digital speech processing. However, a major challenge degrading the robustness of speaker-recognition systems is variation in the emotional states of speakers, such as happiness, anger, sadness, or ...
Ali Hamid Meftah, Hassan Mathkour, Said Kerrache, Yousef Ajami Alotaibi   +3 more
doaj   +1 more source

AVCLNet: Multimodal Multispeaker Tracking Network Using Audio‐Visual Contrastive Learning

CAAI Transactions on Intelligence Technology, Volume 11, Issue 1, Page 238-255, February 2026.
ABSTRACT Audio‐visual speaker tracking aims to determine the locations of multiple speakers in the scene by leveraging signals captured from multisensor platforms. Multimodal fusion methods can improve both the accuracy and robustness of speaker tracking.
Yihan Li, Yidi Li, Zhenhuan Xu, Hao Guo, Mengyuan Liu, Weiwei Wan   +5 more
wiley   +1 more source

TargetGen‐RNN model discovers novel antibiotic compound targeting drug‐resistant Staphylococcus aureus

Interdisciplinary Medicine, Volume 4, Issue 1, January 2026.
TargetGen‐recurrent neural network (RNN), an advanced generative model, generated 28,708 unique and novel compounds, identifying SAK‐2970 as a potent antibiotic against drug‐resistant Staphylococcus aureus. Exhibiting strong biofilm inhibition, high therapeutic efficacy, and minimal systemic toxicity in vivo, SAK‐2970 highlights its safety and clinical
Shakeel Ahmad Khan, Adnan Shakoor, Sadia Kanwal   +2 more
wiley   +1 more source

Real-time arrival picking of rock microfracture signals based on convolutional-recurrent neural network and its engineering application

Journal of Rock Mechanics and Geotechnical Engineering
Accurately picking P- and S-wave arrivals of microseismic (MS) signals in real-time directly influences the early warning of rock mass failure. A common contradiction between accuracy and computation exists in the current arrival picking methods. Thus, a
Bing-Rui Chen, Xu Wang, Xinhao Zhu, Qing Wang, Houlin Xie   +4 more
doaj   +1 more source

Extraction of entity relations from Chinese medical literature based on multi-scale CRNN [PDF]

, 2022
Tingyin Chen, Xuehong Wu, Linyi Li, Jianhua Li, Song Feng   +4 more
openalex   +1 more source

Joint recognition and localization of gunshot based on deep learning [PDF]

Zhihui kongzhi yu fangzhen
In response to the existing gun sound recognition and positioning tasks, which require separate identification and positioning, resulting in time-consuming computation, system redundancy, and complex development processes, this paper proposes to use a ...
MA Mingxing, LI Jian, ZENG Yuan, HE Bin, PANG Runjia
doaj   +1 more source

CRNNs for Urban Sound Tagging with spatiotemporal context

, 2020
This paper describes CRNNs we used to participate in Task 5 of the DCASE 2020 challenge. This task focuses on hierarchical multilabel urban sound tagging with spatiotemporal context. The code is available on our GitHub repository at https://github.com/multitel-ai/urban-sound-tagging.
Arnault, Augustin, Riche, Nicolas
openaire   +2 more sources