OpenAlex Citation Counts

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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:

A Novel Feature Set Extraction Based on Accelerometer Sensor Data for Improving the Fall Detection System
Hong-Lam Le, Duc-Nhan Nguyen, Thi-Hau Nguyen, et al.
Electronics (2022) Vol. 11, Iss. 7, pp. 1030-1030
Open Access | Times Cited: 14

Showing 14 citing articles:

Transformer-based fall detection in videos
Adrián Núñez-Marcos, Ignacio Arganda‐Carreras
Engineering Applications of Artificial Intelligence (2024) Vol. 132, pp. 107937-107937
Open Access | Times Cited: 11

A review of wearable sensors based fall-related recognition systems
Jiawei Liu, Xiaohu Li, Shanshan Huang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 121, pp. 105993-105993
Closed Access | Times Cited: 21

Fall Detection of the Elderly Using Denoising LSTM-Based Convolutional Variant Autoencoder
Myung-Kyu Yi, KyungHyun Han, Seong Oun Hwang
IEEE Sensors Journal (2024) Vol. 24, Iss. 11, pp. 18556-18567
Closed Access | Times Cited: 5

Human Activity Recognition for the Identification of Bullying and Cyberbullying Using Smartphone Sensors
Vincenzo Gattulli, Donato Impedovo, Giuseppe Pirlo, et al.
Electronics (2023) Vol. 12, Iss. 2, pp. 261-261
Open Access | Times Cited: 8

A systematic review on fall detection systems for elderly healthcare
Archana Purwar, Indu Chawla
Multimedia Tools and Applications (2023) Vol. 83, Iss. 14, pp. 43277-43302
Closed Access | Times Cited: 5

Pre-Impact Firefighter Fall Detection Using Machine Learning on the Edge
Xiaoqing Chai, Boon Giin Lee, Matthew Pike, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 13, pp. 14997-15009
Closed Access | Times Cited: 3

Cross dataset non-binary fall detection using a ConvLSTM-attention network
Abbas Shah Syed, Daniel Sierra-Sosa, Anup Kumar, et al.
2022 IEEE Globecom Workshops (GC Wkshps) (2022), pp. 1068-1073
Closed Access | Times Cited: 4

Machine Learning Based Approaches for Cough Detection From Acceleration Signal
Ines Belhaj Messaoud, Elyes Ben Cheikh, Assaad Chiboub, et al.
(2023), pp. 322-328
Open Access | Times Cited: 2

A Data-driven Feature Extraction Method Based on Data Supplement for Human Activity Recognition
Myung-Kyu Yi, Seong Oun Hwang
IEEE Sensors Journal (2024) Vol. 24, Iss. 14, pp. 23311-23323
Closed Access

Human activity recognition by body-worn sensor data using bi-directional generative adversarial networks and frequency analysis techniques
Zohre Kia, Meisam Yadollahzaeh-Tabari, Homayun Motameni
The Journal of Supercomputing (2024) Vol. 81, Iss. 1
Closed Access

Accurate and Efficient Real-World Fall Detection Using Time Series Techniques
Timilehin B. Aderinola, Luca Palmerini, Ilaria D’Ascanio, et al.
Lecture notes in computer science (2024), pp. 52-79
Closed Access

A Novel Attitude Feature Extraction Method for Multi-IMU Based Fall Detection System
Xiaoqing Chai, Boon Giin Lee, Matthew Pike, et al.
(2023)
Closed Access | Times Cited: 1

THE APPLICATION OF MACHINE LEARNING ON THE SENSORS OF SMARTPHONES TO DETECT FALLS IN REAL-TIME
Achraf Benba, Mouna Akki, Sara Sandabad
Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska (2023) Vol. 13, Iss. 2, pp. 50-55
Open Access

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