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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:

Deep learning for sensor-based activity recognition: A survey
Jindong Wang, Yiqiang Chen, Shuji Hao, et al.
Pattern Recognition Letters (2018) Vol. 119, pp. 3-11
Open Access | Times Cited: 1667

Showing 1-25 of 1667 citing articles:

Deep learning for time series classification: a review
Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, et al.
Data Mining and Knowledge Discovery (2019) Vol. 33, Iss. 4, pp. 917-963
Open Access | Times Cited: 2542
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
Wei Yang Bryan Lim, Nguyen Cong Luong, Dinh Thai Hoang, et al.
IEEE Communications Surveys & Tutorials (2020) Vol. 22, Iss. 3, pp. 2031-2063
Open Access | Times Cited: 1816
Deep Learning in Mobile and Wireless Networking: A Survey
Chaoyun Zhang, Paul Patras, Hamed Haddadi
IEEE Communications Surveys & Tutorials (2019) Vol. 21, Iss. 3, pp. 2224-2287
Open Access | Times Cited: 1496
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare
Yiqiang Chen, Xin Qin, Jindong Wang, et al.
IEEE Intelligent Systems (2020) Vol. 35, Iss. 4, pp. 83-93
Open Access | Times Cited: 730
LSTM-CNN Architecture for Human Activity Recognition
Kun Xia, Jianguang Huang, Hanyu Wang
IEEE Access (2020) Vol. 8, pp. 56855-56866
Open Access | Times Cited: 620
Sensor-based and vision-based human activity recognition: A comprehensive survey
L. Minh Dang, Kyungbok Min, Hanxiang Wang, et al.
Pattern Recognition (2020) Vol. 108, pp. 107561-107561
Closed Access | Times Cited: 529
Balanced Distribution Adaptation for Transfer Learning
Jindong Wang, Yiqiang Chen, Shuji Hao, et al.
2021 IEEE International Conference on Data Mining (ICDM) (2017)
Open Access | Times Cited: 525
Progress in wearable electronics/photonics—Moving toward the era of artificial intelligence and internet of things
Qiongfeng Shi, Bowei Dong, Tianyiyi He, et al.
InfoMat (2020) Vol. 2, Iss. 6, pp. 1131-1162
Open Access | Times Cited: 489
Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
Sen Qiu, Hongkai Zhao, Nan Jiang, et al.
Information Fusion (2021) Vol. 80, pp. 241-265
Closed Access | Times Cited: 439
A Comprehensive Survey of Vision-Based Human Action Recognition Methods
Hongbo Zhang, Yi-Xiang Zhang, Bineng Zhong, et al.
Sensors (2019) Vol. 19, Iss. 5, pp. 1005-1005
Open Access | Times Cited: 429
Deep learning-enabled triboelectric smart socks for IoT-based gait analysis and VR applications
Zixuan Zhang, Tianyiyi He, Minglu Zhu, et al.
npj Flexible Electronics (2020) Vol. 4, Iss. 1
Open Access | Times Cited: 313
A survey on wearable sensor modality centred human activity recognition in health care
Yan Wang, Shuang Cang, Hongnian Yu
Expert Systems with Applications (2019) Vol. 137, pp. 167-190
Open Access | Times Cited: 311
Deep learning and big data technologies for IoT security
Mohamed Ahzam Amanullah, Riyaz Ahamed Ariyaluran Habeeb, Fariza Hanum Nasaruddin, et al.
Computer Communications (2020) Vol. 151, pp. 495-517
Closed Access | Times Cited: 302
A survey on video-based Human Action Recognition: recent updates, datasets, challenges, and applications
Preksha Pareek, Ankit Thakkar
Artificial Intelligence Review (2020) Vol. 54, Iss. 3, pp. 2259-2322
Closed Access | Times Cited: 301
Artificial Intelligence‐Enabled Sensing Technologies in the 5G/Internet of Things Era: From Virtual Reality/Augmented Reality to the Digital Twin
Zixuan Zhang, Feng Wen, Zhongda Sun, et al.
Advanced Intelligent Systems (2022) Vol. 4, Iss. 7
Open Access | Times Cited: 295
Human Activity Recognition With Smartphone and Wearable Sensors Using Deep Learning Techniques: A Review
E. Ramanujam, Thinagaran Perumal, S. Padmavathi
IEEE Sensors Journal (2021) Vol. 21, Iss. 12, pp. 13029-13040
Open Access | Times Cited: 286
A spatially explicit deep learning neural network model for the prediction of landslide susceptibility
Dong Van Dao, Abolfazl Jaafari, Mahmoud Bayat, et al.
CATENA (2020) Vol. 188, pp. 104451-104451
Closed Access | Times Cited: 283
Human Activity Recognition Using Inertial, Physiological and Environmental Sensors: A Comprehensive Survey
Florenc Demrozi, Graziano Pravadelli, Azra Bihorac, et al.
IEEE Access (2020) Vol. 8, pp. 210816-210836
Open Access | Times Cited: 280
Deep Learning for Sensor-based Human Activity Recognition
Kaixuan Chen, Dalin Zhang, Lina Yao, et al.
ACM Computing Surveys (2021) Vol. 54, Iss. 4, pp. 1-40
Closed Access | Times Cited: 274
Multi-task Self-Supervised Learning for Human Activity Detection
Aaqib Saeed, Tanır Özçelebi, Johan J. Lukkien
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (2019) Vol. 3, Iss. 2, pp. 1-30
Open Access | Times Cited: 266
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
Kaixuan Chen, Dalin Zhang, Lina Yao, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 259
Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances
Shibo Zhang, Yaxuan Li, Shen Zhang, et al.
Sensors (2022) Vol. 22, Iss. 4, pp. 1476-1476
Open Access | Times Cited: 257
A Survey of Deep Learning-Based Human Activity Recognition in Radar
Xinyu Li, Yuan He, Xiaojun Jing
Remote Sensing (2019) Vol. 11, Iss. 9, pp. 1068-1068
Open Access | Times Cited: 242
Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications
J. M. Górriz, Javier Ramı́rez, Andrés Ortíz, et al.
Neurocomputing (2020) Vol. 410, pp. 237-270
Open Access | Times Cited: 237
FedHome: Cloud-Edge Based Personalized Federated Learning for In-Home Health Monitoring
Qiong Wu, Xu Chen, Zhi Zhou, et al.
IEEE Transactions on Mobile Computing (2020) Vol. 21, Iss. 8, pp. 2818-2832
Open Access | Times Cited: 235
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