在目标检测领域，小样本目标检测（Few-Shot Object Detection, FSOD）一直是个“硬骨头”。传统的做法通常需要在大规模基类数据上预训练，再针对极少数的新类样本进行微调。但微调过程不仅耗时，还容易导致模型对新类样本过拟合。近日，来自澳门大学和英特灵达的研究团队提出了一种全新的框架—— FSOD-VFM 。

Teaching machine learning tools to detect specific objects in a specific image and discount others is a 'game-changer' that could lead to advancements in cancer detection, according to researchers.

AI detects objects in images by using computer vision techniques that analyze the visual features of an image. The process typically involves using a convolutional neural network (CNN) to identify ...