Use | Description | Link | Documentation | |
---|---|---|---|---|
CDeep3M2-Preview: | Extremely quick tests, fully automated instantaneous runs | Link | Documentation | |
CDeep3M2-Docker: | Local or remote, large runs, long trainings, simple installation, GPU with min 12GB vRAM required | Link | Documentation | |
CDeep3M2-AWS: | Remote, large runs, long trainings, simple installation, pay for GPU/hour (entry level 0.50$/h) | Link | Documentation | |
CDeep3M2-Colab: | Remote, short runs or re-training, simple installation, free GPU access | Link | Documentation | |
CDeep3M2-Singularity: | Local or cluster, large runs, long trainings, often required for compute cluster | Link | Documentation |
Training: train the CNN to recognize objects in 3D image stacks (or 2D images)
Transfer Learning: adapt a pre-trained model to a new dataset or different object
For prediction and transfer learning you can use either a pre-trained model from the modelzoo or your own model generated during training.