It depends a bit on your current workflow. If you are detecting the logo and (logo + ) text separately, are you passing them to the same model or are you using a “logo” and another “text” model?
In the former case (one model only), you could try to detect overlapping bounding boxes or ones, which are close to each other, and let the same model create multiple predictions, which can then be either used to calculate the (weighted) prediction.
This workflow would of course be a bit more complicated than using a single input, so in case you would like to start simple (which I would recommend to do), you could try to use the largest box, which should include the logo + text, if possible.