I am working on a project module in which i need to recognize sport objects from the given image for this i am using Neuroph framework's image recognition module and follow this example (http://neuroph.sourceforge.net/image_recognition.html).So for this i first train the system with different basketball images with learning rate=0.5,momentum=0.7, and max error rate=0.01 and also use 12 hidden neurons then give a test image to recognize the basketball from the image But the problem is that it doesnt give me correct results So i am looking for some ideas/suggestions/help on how can i improve/correct my results
Try using learning rate 0.2
Have you managed to train the network at all?
Thanks for the prompt reply, i have used learning rate of 0.2 and its showing me Total Net Error of 0.0495 with 5400 iterations.Also at some point i stop training the network because the Total Net Error isn't affected for certain amount of iteration
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