Visible notion based mostly deep studying transformers for classifying work and images by way of function extraction

Wiratno, T. A. & Callula, B. Transformation of magnificence in digital advantageous arts aesthetics: an artpreneur perspective. APTISI Trans. Technopreneurship. 6, 2, 231–241. (2024).

Google Scholar 

Ardeliya, V. E., Taylor, J. & Wolfson, J. Exploration of synthetic intelligence in artistic fields: generative artwork, music, and design. Int. J. Cyber IT Service Manage. 4 (1), 40–46. (2024).

Google Scholar 

Du, G. et al. Study on automated monitoring system of microwave deicing system for railway contact wire. IEEE Trans. Instrum. Meas. 73 (2024).

Gu, Okay. et al. Perceptual data constancy for high quality Estimation of business pictures. IEEE Trans. Circuits Syst. Video Technol. 35 (1), 477–491. (2025).

Google Scholar 

Wu, J. & Li, H. Artificial intelligence-driven visible function extraction and switch studying for automated identification of work and images. Int. J. Inf. Commun. Technol. 26, 29, 1–18. (2025).

Google Scholar 

Khan, U., Khan, H. U., Iqbal, S. & Munir, H. Four many years of picture processing: a bibliometric evaluation. Libr. Hi Tech. 42 (1), 180–202. (2024).

Google Scholar 

Mahmood, A., Khan, H. U. & Ramzan, M. On modelling for bias-aware sentiment evaluation and its impression in Twitter. J. Web Eng. 19 (1), 1–28. (2020).

Google Scholar 

Bansal, G., Nawal, A., Chamola, V. & Herencsar, N. Revolutionizing visuals: the function of generative AI in fashionable picture era. ACM Trans. Multimedia Comput. Commun. Appl. 20 (11). (2024).

Wang, J. et al. Deep High-Resolution illustration studying for visible recognition. IEEE Trans. Pattern Anal. Mach. Intell. 43 (10), 3349–3364. (2021).

Google Scholar 

Imran, S. et al. Artistic model recognition: combining deep and shallow neural networks for portray classification. Mathematics 11 (22). (2023).

Qiu, H. et al. A novel Delta-Type transformerless unified energy stream controller with a number of energy regulation ports. IEEE Trans. Power Electron. 40 (10), 15820–15834. (2025).

Google Scholar 

Kapetanaki, M. V., Maliagkani, E., Tyrlis, Okay. & Georgalas, I. Artificial intelligence in myopic maculopathy: A complete evaluate of Identification, Classification, and monitoring utilizing various imaging modalities. Cureus 17, 2, e78685. (2025).

Google Scholar 

Naz, A. et al. AI is aware of you: deep studying mannequin for prediction of extroversion character trait. IEEE Access. 1 (2024).

Li, W. Enhanced automated Art curation utilizing supervised modified CNN for Art model classification. Sci. Rep. 15 (1, 7319, ). (2025).

Zhong, S., Huang, X. & Xiao, Z. Fine-art portray classification through two-channel twin path networks. Int. J. Mach. Learn. Cybernet. 11, 1, 137–152. (2020).

Google Scholar 

Xu, G. J. W., Guo, Okay., Park, S. H., Sun, Z. H. & Song, A. Bio-inspired imaginative and prescient mimetics towards next-generation collision-avoidance automation. Innovation 4 (1). (2023).

Zeng, Z., Zhang, S., Qiu, S., Li & Liu, X. A portray authentication methodology based mostly on multi-scale spatial-spectral function fusion and convolutional neural community. Comput. Electr. Eng. 118 (109315). (2024).

Jangtjik, Okay. A., Ho, T. T., Yeh, M. C. & Hua, Okay. L. A CNN-LSTM framework for authorship classification of work, in IEEE International Conference on Image Processing (ICIP), 2017, 2866–2870. (2017). https://doi.org/10.1109/ICIP.2017.8296806

Wang, X., Song, X., Li, Z. & Wang, H. Efficient goal detection in advanced underwater scene pictures based mostly on improved YOLOv8. J. Ocean. Univ. China. 24 (4), 979–992. (2025).

Google Scholar 

Bird, J. J. & Lotfi, A. Image classification and explainable identification of AI-Generated artificial pictures. IEEE Access. 12, 15642–15650. (2024).

Google Scholar 

Xu, H. et al. ESMNet: an enhanced YOLOv7-based method to detect floor defects in precision steel workpieces. Measurement 235 (114970). (2024).

Bharathi Mohan, G. et al. Detecting AI-generated pictures with CNN and Interpretation utilizing Explainable AI, Proceedings of InC4 2024–2024 IEEE International Conference on Contemporary Computing and Communications, (2024). https://doi.org/10.1109/INC460750.2024.10649158

Wang, H. Vision Transformer-Based framework for AI-Generated picture detection in inside design. Informatica 49, 16, 137–150. (2025).

Google Scholar 

Say, T., Alkan, M. & Kocak, A. Advancing GAN Deepfake Detection: Mixed Datasets and Comprehensive Artifact Analysis, Applied Sciences 15, Page 923, 15, 2, 923, 2025, (2025). https://doi.org/10.3390/APP15020923

Martin-Rodriguez, F., Garcia-Mojon, R. & Fernandez-Barciela, M. Detection of AI-Created Images Using Pixel-Wise Feature Extraction and Convolutional Neural Networks, Sensors 23, Page 9037, 23, 22, 9037, 2023, (2023). https://doi.org/10.3390/S23229037

Ahmad Fattah Saskoro, R., Yudistira, N. & Fatyanosa, T. N. Detection of AI-Generated pictures from numerous turbines utilizing gated skilled convolutional neural community. IEEE Access. (2024).

Google Scholar 

Suvarna, V. R., Okay, Y. H., Kumar, N. & Mahamood, S. Okay. Image Forensics: Detecting AI-Generated Images with ML/DL. [Online]. Available: https://www.researchgate.net/publication/390243760

Lađević, A. L., Kramberger, T., Kramberger, R. & Vlahek, D. Detection of AI-Generated Synthetic Images with a Lightweight CNN, AI 5, Pages 1575–1593, 5, 3, 1575–1593, 2024, (2024). https://doi.org/10.3390/AI5030076

Baraheem, S. S. & Nguyen, T. V. AI vs. AI: can AI detect AI-Generated pictures? J. Imaging. 9 (2023). Page 199, 9, 10, 199, 2023.

Chen, Y., Yashtini, M. & Detecting, A. I. Generated Images Through Texture and Frequency Analysis of Patches, 2024 4th International Conference on Artificial Intelligence, Virtual Reality and Visualization, AIVRV 2024, 103–110, (2024). https://doi.org/10.1109/AIVRV63595.2024.10860248

Tan, C., Zhao, Y., Wei, S., Gu, G. & Wei, Y. Learning on Gradients: Generalized Artifacts Representation for GAN-Generated Images Detection.Thecvf.com, 12105–12114, Accessed: 06, 2026 (2023).

Scatigno, C., Teodonio, L., Di Rocco, E. & Festa, G. Spectroscopic benchmarks by machine studying as discriminant evaluation for unconventional Italian pictorialism pictures. Polym. (Basel). 16 (13, 1850, ). (2024).

Zullich, M., MacOvaz, V., Pinna, G. & Pellegrino, F. A. An synthetic intelligence system for automated recognition of punches in Fourteenth-Century panel portray. IEEE Access. 11, 5864–5883. (2023).

Google Scholar 

Chiu, M. C., Hwang, G. J., Hsia, L. H. & Shyu, F. M. Artificial intelligence-supported Art training: a deep learning-based system for selling college college students’ Artwork appreciation and portray outcomes. Interact. Learn. Environ. 32 (3), 824–842. (2024).

Google Scholar 

Lin, H., Van Zuijlen, M., Wijntjes, M. W. A., Pont, S. C. & Bala, Okay. Insights from a large-scale database of fabric depictions in work, Lecture Notes in Computer Science (together with subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12663 LNCS, 531–545, (2021). https://doi.org/10.1007/978-3-030-68796-0_38

Park, J., Kang, H. & Kim, H. Y. Human, do you assume this portray is the work of an actual artist? Int. J. Hum. Comput. Interact. 40, 5174–5191. (2023).

Google Scholar 

Prasetyo, H. D. et al. CNN Architecture on Distinguishing Art and Photo: A Comparison, Proceedings – third International Conference on Informatics, Multimedia, Cyber, and Information System, ICIMCIS 2021, 59–64, (2021). https://doi.org/10.1109/ICIMCIS53775.2021.9699297

Zheng, Y. et al. Fast-zoom and high-resolution sparse compound-eye digital camera based mostly on dual-end collaborative optimization, Opto-Electronic Advances, 8, Issue 6, Pages: 240285-1-240285-12, 8, 6, 240285–1, 2025, (2025). https://doi.org/10.29026/OEA.2025.240285

Gonthier, N., Gousseau, Y. & Ladjal, S. An evaluation of the switch studying of convolutional neural networks for creative pictures, Lecture Notes in Computer Science (together with subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12663 LNCS, 546–561, (2021). https://doi.org/10.1007/978-3-030-68796-0_39

Roullet, C., Fredrick, D., Gauch, J., Vennarucci, R. G. & Loder, W. Transfer Learning Methods for Extracting, Classifying and Searching Large Collections of Historical Images and Their Captions, Lecture Notes in Computer Science (together with subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12667 LNCS, 185–199, (2021). https://doi.org/10.1007/978-3-030-68787-8_13

Agarwal, A. et al. Paintings vs photographs classification utilizing deep studying, Proceedings – International Conference on Technological Advancements in Computational Sciences, ICTACS 922–926, 2023, (2023). https://doi.org/10.1109/ICTACS59847.2023.10390427

Ryabko, B. & Tan, L. Causally-informed instance-wise function choice for explaining visible classifiers. Entropy (2025). 27, Page 814, 27, 8, 814, 2025.

Google Scholar 

Chen, J. et al. 3D floor spotlight removing methodology based mostly on detection masks. Arab. J. Sci. Eng. 1–13. (2025).

Ji, J. et al. DPA-MVSNet: dynamic context notion multi-view stereo with Transformers and knowledge augmentation. Knowl. Based Syst. 325 (113852). (2025).

Xue, X., Hu, H. M., He, Z. & Zheng, H. Towards multi-source illumination coloration fidelity by way of physics-based rendering and spectral energy distribution embedding. IEEE Trans. Comput. Imaging. 11, 1349–1360. (2025).

Google Scholar 

Fan, S. & Zhao, Y. Back to frequent roots: unique creativeness and cultural id in cinematic Macao. Crit. Arts. 39 (3), 90–104. (May 2025).

Luo, T. et al. WFormer: A transformer-based delicate fusion mannequin for strong picture watermarking. IEEE Trans. Emerg. Top. Comput. Intell. 8 (6), 4179–4196. (2024).

Google Scholar 

Wu, X. et al. No-reference level cloud high quality evaluation by way of construction sampling and clustering based mostly on graph. IEEE Trans. Broadcast. 71 (1), 307–322. (2025).

Google Scholar 

Ilyas, M. et al. Using deep studying methods to reinforce blood cell detection in sufferers with leukemia. Inform. (Switzerland). 15 (12). (2024).

Alqahtani, A. et al. A switch studying based mostly method for COVID-19 detection utilizing inception-v4 mannequin. Intell. Autom. Soft Comput. 35, 2, 1721–1736. (2023).

Google Scholar 

Naz, A. et al. Using Transformers and Bi-LSTM with sentence embeddings for prediction of openness human character trait. PeerJ Comput. Sci. 11, e2781. (May 2025).