CNN Semantic segmentation network (UNET) performing poorly when tested with images
Is the dataset public? You can find some good resources and guidance here: https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/UNet_Medical you will find also benchmark results. I think they are usinf ADAM optimizer with 0.0001 learning rate. More details in the training process section.
I am working on building a UNET semantic segmentation network, to detect the iris in eye images we are using DICE loss function and we achieved over 90% train mean IOU and around 87% on validation data but the validation loss and mean IOU showed fluctuation during the 200 epochs, and when we tested our network it showed really poor results, the output image was nothing close to the ground truth even when we used images from the training set it still performed poorly, any suggestions on what we can do to overcome this.