Dont change the meaning rewrite the following paragraph：The feature map input into the ResNest block will be divided into several groups and the number of groups K is a hyperparameter The feature map

The ResNest block divides the feature map input into multiple groups, with the number of groups K being a hyperparameter. The feature map is split into G = KR segments, where K = 2 and R = 2 in this study, as it was found to be the most efficient through ablation experiments. Each split is subjected to convolutional transformations, represented as {F1, F2 ... FG}. Fig 2 shows that after 1×1 convolution, the feature maps split into subsets denoted as x_i, where i∈{1,2,…s}. Each subset x_i has the same spatial size but 1/s number of channels compared to the input feature map, except for 〖 x〗1, which has no corresponding 3×3 convolution. Each subset x_i is subjected to a corresponding 3×3 convolution, denoted as K_i (), and the output is represented as y_i. The feature subset x_i is added to the output of K(i-1)() and fed into K_i (). The transformed features are represented as U_i (). Therefore, U_i () can be expressed as (1)