If these bounding boxes are overlapping, you might want to try decreasing the clustering threshold here: https://github.com/dusty-nv/jetson-inference/blob/19ed62150b3e9499bad2ed6be1960dd38002bb7d/c/detectNet.h#L477
This is the amount of overlap required (in percentage of area) before bounding boxes are clustered. Currently it is set to 75%. After you change it, re-run the following for the change to take effect:
cd jetson-inference/build
make
sudo make install
The images automatically get downsampled to 300x300 before being fed into the SSD-Mobilenet model, so further increasing the source resolutions probably isn’t necessary. Since the object you are trying to detect is on the smaller side, you may want to try training SSD-Mobilenet at 512x512 resolution instead of 300x300. For that, I have a special branch of pytorch-ssd which you can find in this post:
https://forums.developer.nvidia.com/t/how-train-jetson-inference-ssd512-model/168510/6?u=dusty_nv