The output from the convolution blocks is passed to a classification head which converts the outputs into logits and calculates the cross-entropy loss to find the most likely label.
Object detection
DETR, DEtection TRansformer, is an end-to-end object detection model that combines a CNN with a Transformer encoder-decoder.