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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:

A First Look at Deep Learning Apps on Smartphones
Mengwei Xu, Jiawei Liu, Yuanqiang Liu, et al.
(2019)
Open Access | Times Cited: 168

Showing 1-25 of 168 citing articles:

Trends in IoT based solutions for health care: Moving AI to the edge
Luca Greco, Gennaro Percannella, Pierluigi Ritrovato, et al.
Pattern Recognition Letters (2020) Vol. 135, pp. 346-353
Open Access | Times Cited: 280
Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review
Daniel Rosendo, Alexandru Costan, Patrick Valduriez, et al.
Journal of Parallel and Distributed Computing (2022) Vol. 166, pp. 71-94
Open Access | Times Cited: 78
Enable Deep Learning on Mobile Devices: Methods, Systems, and Applications
Han Cai, Ji Lin, Yujun Lin, et al.
ACM Transactions on Design Automation of Electronic Systems (2022) Vol. 27, Iss. 3, pp. 1-50
Open Access | Times Cited: 74
Deep learning based object detection for resource constrained devices: Systematic review, future trends and challenges ahead
Vidya Kamath, A. Renuka
Neurocomputing (2023) Vol. 531, pp. 34-60
Closed Access | Times Cited: 60
Classification and challenges of non-functional requirements in ML-enabled systems: A systematic literature review
Vincenzo De Martino, Fabio Palomba
Information and Software Technology (2025), pp. 107678-107678
Open Access | Times Cited: 2
An Empirical Study Towards Characterizing Deep Learning Development and Deployment Across Different Frameworks and Platforms
Qianyu Guo, Sen Chen, Xiaofei Xie, et al.
2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE) (2019), pp. 810-822
Open Access | Times Cited: 117
DeepWear: Adaptive Local Offloading for On-Wearable Deep Learning
Mengwei Xu, Feng Qian, Mengze Zhu, et al.
IEEE Transactions on Mobile Computing (2019) Vol. 19, Iss. 2, pp. 314-330
Open Access | Times Cited: 107
nn-Meter
Li Lyna Zhang, Shihao Han, Jianyu Wei, et al.
(2021), pp. 81-93
Closed Access | Times Cited: 102
Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data
Chengxu Yang, Qipeng Wang, Mengwei Xu, et al.
(2021), pp. 935-946
Open Access | Times Cited: 92
Occlumency
Taegyeong Lee, Zhiqi Lin, Saumay Pushp, et al.
(2019)
Closed Access | Times Cited: 90
Adversarial XAI Methods in Cybersecurity
Aditya Kuppa, Nhien‐An Le‐Khac
IEEE Transactions on Information Forensics and Security (2021) Vol. 16, pp. 4924-4938
Open Access | Times Cited: 74
PMC
Bingyan Liu, Yuanchun Li, Yunxin Liu, et al.
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (2020) Vol. 4, Iss. 4, pp. 1-25
Closed Access | Times Cited: 71
An Empirical Study on Deployment Faults of Deep Learning Based Mobile Applications
Zhenpeng Chen, Huihan Yao, Yiling Lou, et al.
(2021), pp. 674-685
Open Access | Times Cited: 58
On-Device Deep Learning for Mobile and Wearable Sensing Applications: A Review
Özlem Durmaz İncel, Sevda Özge Bursa
IEEE Sensors Journal (2023) Vol. 23, Iss. 6, pp. 5501-5512
Closed Access | Times Cited: 33
Mobile Foundation Model as Firmware
Jinliang Yuan, Chen Yang, Dongqi Cai, et al.
Proceedings of the 28th Annual International Conference on Mobile Computing And Networking (2024), pp. 279-295
Open Access | Times Cited: 10
A comprehensive survey of deep learning-based lightweight object detection models for edge devices
Payal Mittal
Artificial Intelligence Review (2024) Vol. 57, Iss. 9
Open Access | Times Cited: 10
DeepPayload: Black-box Backdoor Attack on Deep Learning Models through Neural Payload Injection
Yuanchun Li, Jiayi Hua, Haoyu Wang, et al.
(2021), pp. 263-274
Open Access | Times Cited: 49
AsyMo
Manni Wang, Shaohua Ding, Ting Cao, et al.
Proceedings of the 28th Annual International Conference on Mobile Computing And Networking (2021), pp. 215-228
Closed Access | Times Cited: 45
HiveMind: Towards Cellular Native Machine Learning Model Splitting
Song Wang, Xinyu Zhang, Hiromasa Uchiyama, et al.
IEEE Journal on Selected Areas in Communications (2021) Vol. 40, Iss. 2, pp. 626-640
Closed Access | Times Cited: 43
Towards efficient vision transformer inference
Xudong Wang, Li Lyna Zhang, Yang Wang, et al.
(2022), pp. 1-7
Closed Access | Times Cited: 33
A Comprehensive Benchmark of Deep Learning Libraries on Mobile Devices
Qiyang Zhang, Xiang Li, Xiangying Che, et al.
Proceedings of the ACM Web Conference 2022 (2022), pp. 3298-3307
Closed Access | Times Cited: 30
daBNN
Jianhao Zhang, Yingwei Pan, Ting Yao, et al.
Proceedings of the 30th ACM International Conference on Multimedia (2019)
Closed Access | Times Cited: 51
EPASS360: QoE-Aware 360-Degree Video Streaming Over Mobile Devices
Yuanxing Zhang, Yushuo Guan, Kaigui Bian, et al.
IEEE Transactions on Mobile Computing (2020) Vol. 20, Iss. 7, pp. 2338-2353
Closed Access | Times Cited: 39
DeepRec: On-device Deep Learning for Privacy-Preserving Sequential Recommendation in Mobile Commerce
Jialiang Han, Yun Ma, Qiaozhu Mei, et al.
(2021), pp. 900-911
Closed Access | Times Cited: 36
ShadowNet: A Secure and Efficient On-device Model Inference System for Convolutional Neural Networks
Zhichuang Sun, Ruimin Sun, Changming Liu, et al.
2022 IEEE Symposium on Security and Privacy (SP) (2023), pp. 1596-1612
Open Access | Times Cited: 14
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