Table 1 Configuration of the proposed Dynamic-C2f module.

From: Smartphone screen surface defect detection using dynamic large separable kernel attention and multi-scale feature bi-directional path aggregation network

Hyperparameter

Value

Description

Input channels

C1

Number of channels from the previous layer

Output channels

C2

Number of output channels

Number of bottlenecks (n)

3 or 6

Number of Bottleneck_DynamicConv blocks in the module

Bottleneck expansion ratio (e)

0.5

Channel expansion ratio within each bottleneck

Groups (g)

1

Groups for convolution, standard depthwise convolution is not used here

Shortcut connection

True

Whether to use skip connections in the bottleneck

Dynamic convolution layer

DynamicConv

Replaces the standard convolution in the second layer (cv2)

Kernel size (k)

3

Kernel size for the DynamicConv layer

Activation function

SiLU

Default activation used in the DynamicConv block