No title
This thesis presents a novel matching strategy, Inflated Multinomial Matching, which enables training of anchor-free object detection models based on convolutional neural networks. An important aspect of detection models is the integral usage of anchor boxes, where an anchor box is a bounding box with a preset and constant location, size and shape in the image. The matching strategy presented remo
