🎮 Simulator: Manual 2D Convolution
🟢 cross-correlation + bias + ReLU
Fixed 4×4 input, fixed 2×2 kernel (highlighted in blue) — adjust padding (p), stride (s) and bias (b), exactly the parameters EP09_01 asks for as input, and see how they change the output size and values.
Padding (p)
Stride (s)
Bias (b)
(0,0)
Padded input X (with padding)
original
padding (0)
current window
Kernel K (2×2)
Output Y = ReLU(X⊛K + b)
💡 Each slider position reveals one cell of the output matrix. Go through all positions to complete the output map. Changing p, s, or b resets the exploration because the output map changes in size and/or values.
Description: Figure 9.43: EP09_01 Simulator: Manual 2D Convolution (cross-correlation + bias + ReLU, with adjustable padding and stride )