Hi,
There are several improvements you can consider to enhance your classification results:
- Normalize your signals before generating spectrograms to ensure consistent input data.
- You can use "imresize" with an interpolation method like "bilinear" or "bicubic" for better quality.
- Use data augmentation techniques to increase the diversity of your training data, some of those techniques include Time Stretching, Pitch Shifting, Noise Addition etc, you can use "imageDataAugmenter" for augmenting the data.
- Fine-tune the GoogleNet model by training only the last few layers initially, then progressively unfreeze more layers.
Hope this helps!
