Graphic Design Optimization Method Based on Deep Reinforcement Learning Model

[1] Gupta, R., Srivastava, D., Sahu, M., Tiwari, S., Ambasta, R. K., & Kumar, P. (2021). Artificial intelligence to deep learning: Machine intelligence approach for drug discovery. Molecular Diversity, 25(3), 1315-1360. Search in Google Scholar

[2] Song, H., & Montenegro-Marin, C. E. (2021). Secure prediction and assessment of sports injuries using deep learning based convolutional neural network. Journal of Ambient Intelligence and Humanized Computing, 12(3), 3399-3410. Search in Google Scholar

[3] Jacob, I. J., & Darney, P. E. (2021). Design of deep learning algorithm for IoT application by image based recognition. Journal of ISMAC, 3(03), 276-290. Search in Google Scholar

[4] Van der Laak, J., Litjens, G., & Ciompi, F. (2021). Deep learning in histopathology: The path to the clinic. Nature Medicine, 27(5), 775-784. Search in Google Scholar

[5] Bao, Y., & Li, H. (2021). Machine learning paradigm for structural health monitoring. Structural Health Monitoring, 20(4), 1353-1372. Search in Google Scholar

[6] Srivastava, S., Divekar, A. V., Anilkumar, C., Naik, I., Kulkarni, V., & Pattabiraman, V. (2021). Comparative analysis of deep learning image detection algorithms. Journal of Big Data, 8(1), 1-27. Search in Google Scholar

[7] Wang, J., Liu, C., Zheng, L., Jin, M., & Joseph, N. (2022). Research on evaluation of intercultural competence of civil aviation college students based on language operator. Applied Mathematics and Nonlinear Sciences, 7(1), 61-72. Search in Google Scholar

[8] Gao, L., & Wang, M. (2021). The sloshing law of liquid surface for ground rested circular RC tank under unidirectional horizontal seismic action. Applied Mathematics and Nonlinear Sciences, 6(1), 293-306. Search in Google Scholar

[9] Thompson, A. C., Jammal, A. A., Berchuck, S. I., Mariottoni, E. B., & Medeiros, F. A. (2020). Assessment of a segmentation-free deep learning algorithm for diagnosing glaucoma from optical coherence tomography scans. JAMA Ophthalmology, 138(4), 333-339. Search in Google Scholar

[10] Ren, Z., Fang, F., Yan, N., & Wu, Y. (2022). State of the art in defect detection based on machine vision. International Journal of Precision Engineering and Manufacturing-Green Technology, 9(2), 661-691. Search in Google Scholar

[11] Wang, W., Lai, Q., Fu, H., Shen, J., Ling, H., & Yang, R. (2021). Salient object detection in the deep learning era: An in-depth survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(6), 3239-3259. Search in Google Scholar

[12] Sarki, R., Ahmed, K., Wang, H., & Zhang, Y. (2020). Automated detection of mild and multi-class diabetic eye diseases using deep learning. Health Information Science and Systems, 8(1), 1-9. Search in Google Scholar