A Generative Adversarial Network-Based System for Food Appearance Enhancement and Automatic Grading
Keywords:
Food inspection, GAN, Image generation, Automatic grading, YOLOv8, EfficientNet, Deep learningAbstract
The study presents an automated system based on Generative Adversarial Networks (GANs) for food appearance refinement and defect classification. A modified StyleGAN model was trained to generate 20,000 high-resolution food images, thereby expanding the dataset and improving the classification accuracy of rare defect categories by 22%. Using this extended dataset, a two-stage inspection framework was developed. YOLOv8 is applied to detect candidate defect regions, followed by EfficientNet—integrated with an attention mechanism—for classifying defect types with improved sensitivity, particularly for subtle and small-scale flaws. Experiments conducted on a public food image dataset demonstrated that the proposed method achieved a classification accuracy of 94.3%, which is 15.8% higher than conventional CNN-based models. The system also maintained a processing speed of 40 frames per second (FPS), supporting real-time industrial applications. Compared with existing approaches, the method provides more reliable data augmentation, improved model integration, and better adaptability to diverse inspection scenarios, indicating its potential for practical deployment in automated food quality assessment.
References
Wang, Y., Wen, Y., Wu, X., Wang, L., & Cai, H. (2025). Assessing the Role of Adaptive Digital Platforms in Personalized Nutrition and Chronic Disease Management.
Wee, C. S., Ariff, M. S. B. M., Zakuan, N., Tajudin, M. N. M., Ismail, K., & Ishak, N. (2014). Consumers perception, purchase intention and actual purchase behavior of organic food products. Review of integrative business and economics research, 3(2), 378.
Wang, H., Zhang, G., Zhao, Y., Lai, F., Cui, W., Xue, J., ... & Lin, Y. (2024, December). Rpf-eld: Regional prior fusion using early and late distillation for breast cancer recognition in ultrasound images. In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 2605-2612). IEEE.
Wu, X., Sun, Y., & Liu, X. (2024). Multi-class classification of breast cancer gene expression using PCA and XGBoost.
Marimuthu, S., Saikumar, A., & Badwaik, L. S. (2024). Food losses and wastage within food supply chain: A critical review of its generation, impact, and conversion techniques. Waste Disposal & Sustainable Energy, 1-16.
Zhang, T., Zhang, B., Zhao, F., & Zhang, S. (2022, April). COVID-19 localization and recognition on chest radiographs based on Yolov5 and EfficientNet. In 2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP) (pp. 1827-1830). IEEE.
Ziang, H., Zhang, J., & Li, L. (2025). Framework for lung CT image segmentation based on UNet++. arXiv preprint arXiv:2501.02428.
YuChuan, D., Cui, W., & Liu, X. (2024). Head Tumor Segmentation and Detection Based on Resunet.
Wang, Z., Chen, Y., Wang, F., & Bao, Q. (2024, September). Improved Unet model for brain tumor image segmentation based on ASPP-coordinate attention mechanism. In 2024 5th International Conference on Big Data & Artificial Intelligence & Software Engineering (ICBASE) (pp. 393-397). IEEE.
Vepa, A., Yang, Z., Choi, A., Joo, J., Scalzo, F., & Sun, Y. (2024). Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation. Advances in Neural Information Processing Systems, 37, 71643-71671.
Yang, Z., & Zhu, Z. (2024). Curiousllm: Elevating multi-document qa with reasoning-infused knowledge graph prompting. arXiv preprint arXiv:2404.09077.
Li, Z. (2024). Advances in Deep Reinforcement Learning for Computer Vision Applications. Journal of Industrial Engineering and Applied Science, 2(6), 16-26.
Liu, J., Li, K., Zhu, A., Hong, B., Zhao, P., Dai, S., ... & Su, H. (2024). Application of deep learning-based natural language processing in multilingual sentiment analysis. Mediterranean Journal of Basic and Applied Sciences (MJBAS), 8(2), 243-260.
Tang, X., Wang, Z., Cai, X., Su, H., & Wei, C. (2024, August). Research on heterogeneous computation resource allocation based on data-driven method. In 2024 6th International Conference on Data-driven Optimization of Complex Systems (DOCS) (pp. 916-919). IEEE.
Qiao, J. B., Fan, Q. Q., Xing, L., Cui, P. F., He, Y. J., Zhu, J. C., ... & Jiang, H. L. (2018). Vitamin A-decorated biocompatible micelles for chemogene therapy of liver fibrosis. Journal of Controlled Release, 283, 113-125.
Qu, G., Hou, S., Qu, D., Tian, C., Zhu, J., Xue, L., ... & Zhang, C. (2019). Self-assembled micelles based on N-octyl-N’-phthalyl-O-phosphoryl chitosan derivative as an effective oral carrier of paclitaxel. Carbohydrate polymers, 207, 428-439.
Zhu, J., Xie, R., Gao, R., Zhao, Y., Yodsanit, N., Zhu, M., ... & Gong, S. (2024). Multimodal nanoimmunotherapy engages neutrophils to eliminate Staphylococcus aureus infections. Nature Nanotechnology, 1-12.
Lee, I. K., Xie, R., Luz-Madrigal, A., Min, S., Zhu, J., Jin, J., ... & Ma, Z. (2023). Micromolded honeycomb scaffold design to support the generation of a bilayered RPE and photoreceptor cell construct. Bioactive Materials, 30, 142-153.
Yodsanit, N., Shirasu, T., Huang, Y., Yin, L., Islam, Z. H., Gregg, A. C., ... & Wang, B. (2023). Targeted PERK inhibition with biomimetic nanoclusters confers preventative and interventional benefits to elastase-induced abdominal aortic aneurysms. Bioactive materials, 26, 52-63.
Wang, Y., Wen, Y., Wu, X., & Cai, H. (2024). Application of Ultrasonic Treatment to Enhance Antioxidant Activity in Leafy Vegetables. International Journal of Advance in Applied Science Research, 3, 49-58.
Liu, Z., Costa, C., & Wu, Y. (2024). Quantitative Assessment of Sustainable Supply Chain Practices Using Life Cycle and Economic Impact Analysis.
Zhu, J., Xu, T., Zhang, Y., & Fan, Z. (2024). Scalable Edge Computing Framework for Real-Time Data Processing in Fintech Applications. International Journal of Advance in Applied Science Research, 3, 85-92.
Wang, Y., Shen, M., Wang, L., Wen, Y., & Cai, H. (2024). Comparative Modulation of Immune Responses and Inflammation by n-6 and n-3 Polyunsaturated Fatty Acids in Oxylipin-Mediated Pathways.
Wang, Y., Wen, Y., Wu, X., Wang, L., & Cai, H. (2024). Modulation of Gut Microbiota and Glucose Homeostasis through High-Fiber Dietary Intervention in Type 2 Diabetes Management.
Wang, Y., Wen, Y., Wu, X., & Cai, H. (2024). Comprehensive Evaluation of GLP1 Receptor Agonists in Modulating Inflammatory Pathways and Gut Microbiota.
Varghese, R., & Sambath, M. (2024, April). Yolov8: A novel object detection algorithm with enhanced performance and robustness. In 2024 International Conference on Advances in Data Engineering and Intelligent Computing Systems (ADICS) (pp. 1-6). IEEE.
Liu, Z., Costa, C., & Wu, Y. (2024). Leveraging Data-Driven Insights to Enhance Supplier Performance and Supply Chain Resilience.
Wang, Y., Wang, L., Wen, Y., Wu, X., & Cai, H. (2025). Precision-Engineered Nanocarriers for Targeted Treatment of Liver Fibrosis and Vascular Disorders.
Zhu, J., Wu, Y., Liu, Z., & Costa, C. (2025). Sustainable Optimization in Supply Chain Management Using Machine Learning. International Journal of Management Science Research, 8(1).
Liu, Z., Costa, C., & Wu, Y. (2024). Data-Driven Optimization of Production Efficiency and Resilience in Global Supply Chains. Journal of Theory and Practice of Engineering Science, 4(08), 23-33.
Aldeer, M., Sun, Y., Pai, N., Florentine, J., Yu, J., & Ortiz, J. (2023, May). A Testbed for Context Representation in Physical Spaces. In Proceedings of the 22nd International Conference on Information Processing in Sensor Networks (pp. 336-337).
Che Azemin, M. Z., Mohd Tamrin, M. I., Hilmi, M. R., & Mohd Kamal, K. (2024, February). Assessing the efficacy of StyleGAN 3 in generating realistic medical images with limited data availability. In Proceedings of the 2024 13th International Conference on Software and Computer Applications (pp. 192-197).
