Expired50% confidenceFactExact time

For a convolutional layer with kernel size k×k, C_in input channels, and C_out output channels, the number of floating-point operations is approximately 2×k²×C_in×C_out×H×W.

1

Sources

50%

Confidence

Medium-term (~90 days)

Relevance

7/2/2026

First Seen

Valid until: 9/30/2026(expired)

Sources

PyTorch Image Classification in Practice: Complete Pipeline from Data Preprocessing to Model Training

bilibili程序员是魔法师AI-bx6/17/2026

Related Claims

UnverifiedThe architecture of LeNet-5 includes the C1 layer (6 5×5 convolution kernels, output 6@28×28), the S2 layer (2×2 average pooling, output 6@14×14), the C3 layer (16 5×5 convolution kernels, output 16@10×10), the S4 layer (2×2 average pooling, output 16@5×5), the C5 layer (120 5×5 convolution kernels), the F6 fully connected layer (84 neurons), and the output layer (10 nodes).61% similar

Cite This Claim

Stable URI

https://kongchang.com/claim/45215

API

curl https://kongchang.com/api/v1/knowledge/claims/45215

MCP

get_claim(id=45215)