Pruning rate-controlled filter order–information structure similarity graph clustering for DCNN structure optimization methods-Reference-Cited by-同舟云学术

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Pruning rate-controlled filter order–information structure similarity graph clustering for DCNN structure optimization methods

Published:2024-02-23 Issue:32 Volume:83 Page:78407-78431
ISSN:1573-7721
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Pei Jihong,Huang Zhengliang,Zhu Jihong^ORCID

Funder

the National Natural Science Foundation of China

the Shenzhen Science and Technology Project

the PHD Research Foundation of Gannan Normal University

the science and technology project of the education department of Jiangxi province

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11042-024-18615-z.pdf

Reference42 articles.

1. Jegan R, Vijayakumar P, Ambethkumar V, Vijay P, Onyema EM (2023) Encryption and decryption of a word into weighted graph using super-edge anti-magic total labeling of bi-star graph

2. Ma L, Gupta RK, Onyema EM (2022) Optimization of intelligent network information management system under big data and cloud computing. Scalable Comput Pract Exp 23(3):91–101

3. Burhan M, Alam H, Arsalan A, Rehman RA, Anwar M, Faheem M, Ashraf MW (2023) A comprehensive survey on the cooperation of fog computing paradigm-based iot applications: layered architecture, real-time security issues, and solutions. IEEE Access

4. Raza B, Aslam A, Sher A, Malik AK, Faheem M (2020) Autonomic performance prediction framework for data warehouse queries using lazy learning approach. Appl Soft Comput 91:106216

5. Malik H, Anees T, Faheem M, Chaudhry MU, Ali A, Asghar MN (2023) Blockchain and internet of things in smart cities and drug supply management: Open issues, opportunities, and future directions. Internet of Things, pp 100860

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