Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

RNN- and LSTM-Based Soft Sensors Transferability for an Industrial Process
Francesco Curreri, Luca Patanè, Maria Gabriella Xibilia
Sensors (2021) Vol. 21, Iss. 3, pp. 823-823
Open Access | Times Cited: 61

Showing 1-25 of 61 citing articles:

LSTM-Autoencoder for Vibration Anomaly Detection in Vertical Carousel Storage and Retrieval System (VCSRS)
Jae Seok, Akeem Bayo Kareem, Jang-Wook Hur
Sensors (2023) Vol. 23, Iss. 2, pp. 1009-1009
Open Access | Times Cited: 33
LSTM Short-Term Wind Power Prediction Method Based on Data Preprocessing and Variational Modal Decomposition for Soft Sensors
Peng Lei, Fanglan Ma, Changsheng Zhu, et al.
Sensors (2024) Vol. 24, Iss. 8, pp. 2521-2521
Open Access | Times Cited: 9
A Review on AI for Smart Manufacturing: Deep Learning Challenges and Solutions
Jiawen Xu, Matthias Kovatsch, Denny Mattern, et al.
Applied Sciences (2022) Vol. 12, Iss. 16, pp. 8239-8239
Open Access | Times Cited: 32
A Survey and Perspective on Industrial Cyber-Physical Systems (ICPS): From ICPS to AI-Augmented ICPS
Jiyeong Chae, Sanghoon Lee, Junhyung Jang, et al.
IEEE Transactions on Industrial Cyber-Physical Systems (2023) Vol. 1, pp. 257-272
Open Access | Times Cited: 21
Artificial intelligence-based forecasting model for incinerator in sulfur recovery units to predict SO2 emissions
Muhammed Thameem, Abhijeet Raj, Abdallah S. Berrouk, et al.
Environmental Research (2024) Vol. 249, pp. 118329-118329
Closed Access | Times Cited: 6
A deep hybrid network for significant wave height estimation
Luca Patanè, Claudio Iuppa, Carla Faraci, et al.
Ocean Modelling (2024) Vol. 189, pp. 102363-102363
Open Access | Times Cited: 6
Soft Sensor Transferability: A Survey
Francesco Curreri, Luca Patanè, Maria Gabriella Xibilia
Applied Sciences (2021) Vol. 11, Iss. 16, pp. 7710-7710
Open Access | Times Cited: 34
Supervised Attention-Based Bidirectional Long Short-Term Memory Network for Nonlinear Dynamic Soft Sensor Application
Zeyu Yang, Ruining Jia, Peiliang Wang, et al.
ACS Omega (2023) Vol. 8, Iss. 4, pp. 4196-4208
Open Access | Times Cited: 15
rAAV Manufacturing: The Challenges of Soft Sensing during Upstream Processing
Cristovão Freitas Iglesias, Miliça Ristovski, Miodrag Bolić, et al.
Bioengineering (2023) Vol. 10, Iss. 2, pp. 229-229
Open Access | Times Cited: 13
Multi-modal temporal action segmentation for manufacturing scenarios
Laura Romeo, Roberto Marani, Anna Gina Perri, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 148, pp. 110320-110320
Open Access
Deep learning models for forecasting sour gas generation in a petroleum refinery
Balakrishnan Dharmalingam, Gnanaprakasam Arul Jesu, Thirumarimurugan Marimuthu
The Canadian Journal of Chemical Engineering (2025)
Closed Access
Semisupervised dynamic soft sensor based on complementary ensemble empirical mode decomposition and deep learning
Runyuan Guo, Han Liu
Measurement (2021) Vol. 183, pp. 109788-109788
Closed Access | Times Cited: 26
Domain Adversarial Neural Network Regression to design transferable soft sensor in a power plant
Hossein Shahabadi Farahani, Alireza Fatehi, Alireza Nadali, et al.
Computers in Industry (2021) Vol. 132, pp. 103489-103489
Closed Access | Times Cited: 25
Stable soft sensor modeling based on causality analysis
Feng Yu, Qiluo Xiong, Liang Cao, et al.
Control Engineering Practice (2022) Vol. 122, pp. 105109-105109
Closed Access | Times Cited: 18
A comprehensive data analysis for aggregate capacity forecasting in Vehicle-to-Grid applications
Luca Patanè, Francesca Sapuppo, Maria Gabriella Xibilia, et al.
(2024), pp. 1-6
Closed Access | Times Cited: 3
The TPRF: A Novel Soft Sensing Method of Alumina–Silica Ratio in Red Mud Based on TPE and Random Forest Algorithm
Fanguang Meng, Zhiguo Shi, Yongxing Song
Processes (2024) Vol. 12, Iss. 4, pp. 663-663
Open Access | Times Cited: 2
Speaker Identification Using Hybrid Subspace, Deep Learning and Machine Learning Classifiers
Serkan Keser
(2024)
Open Access | Times Cited: 2
Predictive Models for Aggregate Available Capacity Prediction in Vehicle-to-Grid Applications
Luca Patanè, Francesca Sapuppo, G. Napoli, et al.
Journal of Sensor and Actuator Networks (2024) Vol. 13, Iss. 5, pp. 49-49
Open Access | Times Cited: 2
Synthesizing labeled data to enhance soft sensor performance in data-scarce regions
Yuting Lyu, Junghui Chen, Zhihuan Song
Control Engineering Practice (2021) Vol. 115, pp. 104903-104903
Closed Access | Times Cited: 17
Developing accurate data-driven soft-sensors through integrating dynamic kernel slow feature analysis with neural networks
Jeremiah Corrigan, Jie Zhang
Journal of Process Control (2021) Vol. 106, pp. 208-220
Open Access | Times Cited: 17
Transfer Learning in wastewater treatment plants control: Measuring the transfer suitability
Ivan Pisa, Antoni Morell, José López Vicario, et al.
Journal of Process Control (2023) Vol. 124, pp. 36-53
Open Access | Times Cited: 6
Critical measurement parameters estimation in liquid rocket engine using LSTM-based soft sensor
Gilbert Chandra D., M. Devakumar, U. Srinivasulu Reddy, et al.
Flow Measurement and Instrumentation (2023) Vol. 92, pp. 102371-102371
Closed Access | Times Cited: 6
Deep transfer learning methods for typical supervised tasks in industrial monitoring: state-of-the-art, challenges, and perspectives
铮 柴, 嘉业 汪, Chunhui Zhao, et al.
Scientia Sinica Informationis (2023) Vol. 53, Iss. 5, pp. 821-821
Closed Access | Times Cited: 6
Transfer Learning in Wastewater Treatment Plant Control Design: From Conventional to Long Short-Term Memory-Based Controllers
Ivan Pisa, Antoni Morell, Ramón Vilanova, et al.
Sensors (2021) Vol. 21, Iss. 18, pp. 6315-6315
Open Access | Times Cited: 15
A systematic review on application of deep learning in digestive system image processing
Huangming Zhuang, Jixiang Zhang, Fei Liao
The Visual Computer (2021) Vol. 39, Iss. 6, pp. 2207-2222
Open Access | Times Cited: 13
Page 1 - Next Page

Scroll to top