What is vanishing gradient problem in CNNs and how is it solved?

Vanishing gradients occur when gradients become too small in deep networks, slowing or stopping learning in early layers.

In deep CNNs, repeated multiplication of small gradients during backpropagation causes them to shrink exponentially. This prevents early layers from learning effectively. Solutions include ReLU activation, batch normalization, residual connections, and better weight initialization strategies.