- Increase mini-batch size : Increasing the mini batch size can speed up training and reduce the variance of the model.
- Data augmentation : By using Data augmentation techniques like flipping, rotation, resizing can help you to improve the performance of your model.
- Adjust learning-rate – Experiment with learning rate might be helpful.
- Adjust hyper-parameters : You can consider changing the hyperparameters such as number of epochs, number of layers in your mode, optimization algorithm .
Which paramaters can improve detector performance?
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Hello everyone, I trained Faster RCNN and SSD object detectors with my own dataset with 5 classes… My results are: Faster RCNN average precision 64% and SSD average precision 45% … I was inspirated by examples on matworks page… which parameters should I change or increase to get better results? I mean if increasing minibatchsize would give me better average precision or what should i change ? Thanks for answers… I mean which parameters in training options can improve my results?
Sachin el 5 de Jun. de 2023
I understand that you want to improve the detector performance.
Following suggestions might be helpful to you:
Refer the following MATLAB Documentation page :