AI RESEARCH
How to Choose Your Teacher for Fine Grained Image Recognition
arXiv CS.CV
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ArXi:2605.15689v1 Announce Type: new Fine-grained image recognition classifies subcategories such as bird species or car models. While state-of-the-art (SOTA) models are accurate, they are often too resource-intensive for deployment on constrained devices. Knowledge distillation addresses this by transferring knowledge from a large teacher model to a smaller student model. A key challenge is selecting the right teacher, as it heavily impacts student performance. This paper