{"id":138,"date":"2025-05-31T16:24:14","date_gmt":"2025-05-31T16:24:14","guid":{"rendered":"https:\/\/sites.wp.odu.edu\/cyberimpact1\/?page_id=138"},"modified":"2025-06-12T18:28:47","modified_gmt":"2025-06-12T18:28:47","slug":"cyse-368","status":"publish","type":"page","link":"https:\/\/sites.wp.odu.edu\/huongq\/cyse-368\/","title":{"rendered":"National Science Foundation"},"content":{"rendered":"

Machine learning internship\"\"<\/h1>\n

I had the privilege of participating in the undergraduate research experience, where I learned how to train a machine learning model. During this program, I gained insights into the mechanisms of training AI systems, particularly through hands-on experiments with convolutional neural networks, image classifiers, and adversarial patches. I tackled challenging tasks that involved training models for image classification and deception using diverse datasets, fine-tuning loss functions, and leveraging the computational power of the NVIDIA Jetson Nano. A highlight of my work was the development of a robust shaped patch, able to effectively fool the YOLOv2 model!<\/p>\n

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\u00a0<\/p>\n<\/div>\n\n31-Shaped-Adversarial-Patches<\/a>\n

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Machine learning internship I had the privilege of participating in the undergraduate research experience, where I learned how to train a machine learning model. During this program, I gained insights into the mechanisms of training AI systems, particularly through hands-on experiments with convolutional neural networks, image classifiers, and adversarial patches. I tackled challenging tasks that… <\/p>\n

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