FUSION OF DEEP CONVOLUTIONAL NETWORKS AND UNSUPERVISED METHODS IN ACCURATE GRAPH PARSING

Wenhao Wen

References

  1. [1] X. Zhou, Application and analysis of computer visionalgorithms in graphics and image processing, InternationalJournal of Informatics and Information Systems, 6(1), 2023,8–15.
  2. [2] C. Li and G. Baciu, VisFM: Visual analysis of image featurematchings, Computer Graphics Forum, 38(1), 2019, 46–58.
  3. [3] R. Chen and C. Ren, Correlation alignment with attentionmechanism for unsupervised domain adaptation, Web Intelli-gence, IOS Press, 18(4), 2020, 261–267.
  4. [4] M. Gheisari, H. Hamidpour, Y. Liu, P. Saedi, A. Raza, A.Jalili, H. Rokhsati, and R. Amin, Data mining techniques forweb mining: A survey, Artificial Intelligence and Applications,1(1), 2023, 3–10.
  5. [5] R.N. Abirami, P.M. Durai Raj Vincent, K. Srinivasan, U. Tariq,and C.Y. Chang, Deep CNN and deep GAN in computationalvisual perception-driven image analysis, Complexity, 21(12),2021, 1–30.
  6. [6] S. Hayat, S. Kun, S. Shahzad, P. Suwansrikham, M. Mateen,and Y. Yu, Entropy information-based heterogeneous deepselective fused features using deep convolutional neural networkfor sketch recognition, IET Computer Vision, 15(3), 2021,165–180.
  7. [7] M.F. Danca, P. Bourke, and N. Kuznetsov, Graphicalstructure of attraction basins of hidden chaotic attractors:The Rabinovich-Fabrikant system, International Journal ofBifurcation and Chaos, 29(1), 2019, 1–13.
  8. [8] P.B. Siti, M. Mustaji, B. Bachri, and F.D. Patricia, Buildingempathy: Exploring digital native characteristic to createlearning instruction for learning computer graphic design,International Journal of Emerging Technologies in Learning,15(20), 2020, 145–159.
  9. [9] I. Wasyluk and G. Koziel, The analysis of the influence of agraphical user interface’s design on the number and time ofwebsite visits, Journal of Computer Sciences Institute, 12(6),2019, 187–192.
  10. [10] V. Cviljuˇsac, A.L. Brki´c, A. Divjak, and D. Modric, Utilizingstandard high-resolution graphic computer-to-film process forcomputer-generated hologram printing, Applied Optics, 58(34),2019, 143–148.
  11. [11] H Yeom, Y. Ko, and J. Seo, Unsupervised-learning-basedkeyphrase extraction from a single document by the effectivecombination of the graph-based model and the modified C-value method, Computer Speech & Language, 58(3), 2019,304–318.
  12. [12] M. Fares, A. Moufarrej, E. Jreij, J. Tekli, and W. Grosky,Unsupervised word-level affect analysis and propagation in alexical knowledge graph, Knowledge-Based Systems, 165(10),2019, 432–459.
  13. [13] T. Mao, Z. Shi, and D.X. Zhou, Approximating functions withmulti-features by deep convolutional neural networks, Analysisand Applications, 21(1), 2023, 93–125.
  14. [14] Y. Lin, S. Li, J. Xu, J. Xu, D. Huang, W. Zheng, Y. Cao, andJ. Lu, Graph over-parameterization: Why the graph helps thetraining of deep graph convolutional network, Neurocomputing,534(9), 2023, 77–85.
  15. [15] M. Shao, Y. Zhang, Y. Fan, W. Zuo, and D. Meng, IIT-GAT:Instance-level image transformation via unsupervised gener-ative attention networks with disentangled representations,Knowledge-Based Systems, 225(5), 2021, 1–12.
  16. [16] P. Wei, C. Zhang, Y. Tang, Z. Li, and Z. Wang, Reinforceddomain adaptation with attention and adversarial learning forunsupervised person Re-ID, Applied Intelligence, 53(4), 2023,4109–4123.
  17. [17] Z. Lei, Y. Wang, Z. Li, and J. Yang, Attention based multilayerfeature fusion convolutional neural network for unsupervisedmonocular depth estimation, Neurocomputing, , 423(6), 2021,343–352.
  18. [18] Z. Wei and Y. Liu, Construction of super-resolution modelof remote sensing image based on deep convolutional neuralnetwork, Computer Communications, 178(10), 2021, 191–200.
  19. [19] A. Taouli, D.A. Bensaber, K. Bencherif, and N. Keskes,Semantics convolutional neural network for medical imagesanalysis, Revue d’Intelligence Artificielle, 36(2), 2022,279–288.9
  20. [20] J. Chen, Classification and model method of convolutionalfeatures in sketch images based on deep learning, InternationalJournal of Pattern Recognition and Artificial Intelligence,36(12), 2022, 1–19.
  21. [21] X.Q. Gui, Y. Zhang, and L. Li, Image style migration basedon cyclegan with same mapping loss, International Journal ofRobotics and Automation, 39(1), 2024, 1048-1052.
  22. [22] P. Yang, S. Xiao, R. Wu, and H. Lin, A Spatial positioningmethod of light absorbing material object for volutedepalletising system based on RGB-D camera, InternationalJournal of Robotics and Automation, , 39(6), 2024, 1162–1164.

Important Links:

Go Back