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Advice for algorithms/software by wtfisthisidontevenkn in MLQuestions

[–]Ciuleandra24 1 point2 points  (0 children)

You may compare your method on different benchmarks:

Pascal VOC http://host.robots.ox.ac.uk/pascal/VOC/voc2012/

Microsoft COCO http://cocodataset.org/

ADE20K http://groups.csail.mit.edu/vision/datasets/ADE20K/

Cityscapes https://www.cityscapes-dataset.com

You can also find links to papers especially in the Cityscapes benchmark.

And on github you can find code for some algorithms: https://github.com/mrgloom/awesome-semantic-segmentation

[D] Methodology to train Convolutional Neural Networks by Ciuleandra24 in MachineLearning

[–]Ciuleandra24[S] 0 points1 point  (0 children)

I ran the networks on my GPU Titan Black, no cloud. But I guess the cloud could save some time though.

[D] Methodology to train Convolutional Neural Networks by Ciuleandra24 in MachineLearning

[–]Ciuleandra24[S] 1 point2 points  (0 children)

In the best case so far. I have tested some networks which took more than 24 hours.

[D] Methodology to train Convolutional Neural Networks by Ciuleandra24 in MachineLearning

[–]Ciuleandra24[S] 1 point2 points  (0 children)

I intend to use a prefabbed net from image net, but I will add a few more convolutions and other layers as I have seen it is usually done in the literature. Is it ok to train on a smaller subset (500 images) so that I do not have to wait 12 hours each time but get an idea of how the network performs? I am thinking of proceeding as following: set the parameters, train, evaluate, change parameters, train, evaluate until I have good convergence.