3 accepted papers
Traditional supervised learning heavily relies on human-annotated datasets, especially in data-hungry neural approaches. However, various tasks, especially multi-label tasks like document-level relation extraction, pose challenges in fully manual annotation due to the specific domain knowledge and l…
Point-based cell detection (PCD), which pursues high-performance cell sensing under low-cost data annotation, has garnered increased attention in computational pathology community. Unlike mainstream PCD methods that rely on intermediate density map representations, the Point-to-Point network (P2PNet…
Fine-grained visual classification (FGVC) intends to confirm the sub-classes of a specific object category, e.g., identifying the species of dogs or birds. It is a challenging problem with the inter-class similarity among these sub-categories and intra-class variance in every fine-grained class. Mos…