3 accepted papers
In knowledge distillation, the performance of teacher models often serves as an upper limit for student models. For a long time, deeper and more accurate supervised learning algorithms have been the first choice for teacher models in image classification tasks where unsupervised models typically und…
Recent advances in oracle bone inscriptions (OBI) classification have explored various strategies such as zero-shot learning, augmentation, and complex convolution architectures. These strategies ultimately represent samples as global feature vectors in various forms but often fail to effectively ca…
Understanding and identifying the nature of learner confusion is important for online learning platforms. In this study, we address this problem by analyzing forum posts from large-scale online courses. However, due to the large volume of comments and frequent interactions, confusion posts are often…