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, overlap, and NFFT are specified in seconds.

   • Bout length: calls within this distance are placed into a single image.

     • If value is not equal to zero, only a single file can be processed at a time.

   • 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 faster-RCNN detector: (USE 2018a! DOES NOT WORK IN 2018b)

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"