Training Detection Networks

To create an image database for training a faster-RCNN detector:

1. Select "Tools > Network Training > Create Network Training Images"

2. In the dialog box, select all files to create images from.

3. Enter spectrogram settings.

   • FTT windows length and NFFT are specified in seconds.

     • Tip: Set [Focus] window to the image length you want to create and use the auto spectrogram settings in the [Display Settings] button to determine the best settings.

4. Enter image length.

   • Images should fit a couple calls comfortably. 1/2 second good for short USVs

5. Select number of augmented duplicates.

   • The number of times to duplicate each image, with random amplitude and scaling modification.
   • This feature increases the size and variability of training sets to increase generalizability.

To train a Yolo V2 detector: (Use 2020a or later)

1. Select "Tools > Network Training > Train Network"

2. In the dialog box, select all training tables from which to train from (saved in "DeepSqueak\Training\").

3. Decide whether or not to use a pre-trained network as the starting point.

4. Training will take hours. When finished a save dialog will appear.

For advanced users: To change the network architecture, edit "TrainSqueakDetector.m"