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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 novel 5D brain parcellation approach based on spatio-temporal encoding of resting fMRI data from deep residual learning
Behnam Kazemivash, Vince D. Calhoun
Journal of Neuroscience Methods (2022) Vol. 369, pp. 109478-109478
Open Access | Times Cited: 11

Showing 11 citing articles:

A comparative study of attention mechanism based deep learning methods for bladder tumor segmentation
Qi Zhang, Yinglu Liang, Yi Zhang, et al.
International Journal of Medical Informatics (2023) Vol. 171, pp. 104984-104984
Closed Access | Times Cited: 20
Themis
Saeed Rashidi, William Won, Sudarshan Srinivasan, et al.
(2022)
Open Access | Times Cited: 12
Application of deep learning in fMRI-based human brain parcellation: a review
Yu Li, Xun Chen, Qinrui Ling, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 3, pp. 032001-032001
Closed Access | Times Cited: 4
Construction of a thinking model for Literary Writing based on Deep Spatio-Temporal Residual Convolutional Neural Networks
Xiaoyang Ren
Multimedia Tools and Applications (2024) Vol. 83, Iss. 27, pp. 69467-69488
Closed Access | Times Cited: 1
A deep residual model for characterization of 5D spatiotemporal network dynamics reveals widespread spatiodynamic changes in schizophrenia
Behnam Kazemivash, Theo G.M. van Erp, Peter Kochunov, et al.
Frontiers in Neuroimaging (2023) Vol. 2
Open Access | Times Cited: 2
RefineNet: An Automated Framework to Generate Task and Subject-Specific Brain Parcellations for Resting-State fMRI Analysis
Naresh Nandakumar, Komal Manzoor, Shruti Agarwal, et al.
Lecture notes in computer science (2022), pp. 315-325
Closed Access | Times Cited: 4
fMRI-based spatio-temporal parcellations of the human brain
Qinrui Ling, Aiping Liu, Yu Li, et al.
Current Opinion in Neurology (2024) Vol. 37, Iss. 4, pp. 369-380
Closed Access
st-DenseViT: A Weakly Supervised Spatiotemporal Vision Transformer for Dense Prediction of Dynamic Brain Networks
Behnam Kazemivash, Pranav Suresh, Dong Hye Ye, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
A 5D approach to study spatio-temporal dynamism of resting-state brain networks in schizophrenia
Behnam Kazemivash, Vince D. Calhoun
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2022), pp. 3737-3740
Closed Access | Times Cited: 2
Impact of RoCE Congestion Control Policies on Distributed Training of DNNs
Tarannum Khan, Saeed Rashidi, Srinivas Sridharan, et al.
(2022), pp. 39-48
Open Access | Times Cited: 2
A deep residual model for characterization of 5D spatiotemporal network dynamics reveals widespread spatiodynamic changes in schizophrenia
Behnam Kazemivash, Theo G. M. vanErp, Peter Kochunov, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 1
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