Multiple merging multiple convolutions
What you describe sounds a lot like the inception module. You can use Keras to concatenate convolutions with different filter sizes acting on the same input, such as:



This will increase the compute time, but might give you what you want. Above image is taken from here, where you can also find the code for building such modules using Keras in the section titled How to Implement the Inception Module.