Methods > Computer Vision > Convolutional Neural Networks

Darknet-19

Introduced by Redmon et al. in YOLO9000: Better, Faster, Stronger

Darknet-19 is a convolutional neural network that is used as the backbone of YOLOv2. Similar to the VGG models it mostly uses $3 \times 3$ filters and doubles the number of channels after every pooling step. Following the work on Network in Network (NIN) it uses global average pooling to make predictions as well as $1 \times 1$ filters to compress the feature representation between $3 \times 3$ convolutions. Batch Normalization is used to stabilize training, speed up convergence, and regularize the model batch.

Source: YOLO9000: Better, Faster, Stronger

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