HyperConnect, Seoul, South Korea
Research Scientist Internship

  • Trained a classification model to filter inappropriate profile pictures in Azar.
  • Developed an image classification model to automatically filter inappropriate images from a large-scale, imbalanced dataset over millions of images.
  • Improved the existing Inception-ResNet V2 model by replacing it with EfficientNet-V5, achieving an accuracy of 96.51%.
  • Researched and applied various self-supervised learning techniques, such as Data Distillation and Label Refinery, to address data imbalance and noise issues.