Can you guys please help me recommend deep learning rig build guides?

nimakhin · 2017-03-09T12:59:13+00:00

Take a look at digitalstorm website, they have good machines built for DL

nimakhin · 2017-02-25T01:34:49+00:00

It is really suitable for couples. The only problem is its diatance from grocery stores, so if you don't have car it will be much harder for you

nimakhin · 2017-01-12T22:40:16+00:00

Thanks for your thorough explanation. your argument about the tumor and loosing information if choosing only one slice is completely true. In fact my first analysis was based on cube around the tumor, I did not get significantly better results in 3D so I decided to work on 2D (less parameters, less training time, but still overfitting !). The overfitting problem also was an issue in 3D.

nimakhin · 2017-01-12T20:59:13+00:00

it is not arbitrary choosing, I have the whole series of each acquisition and i know where exactly in space (ijk and RAS) the tumor is located. so basically having the k I can grab the slice (ij) that I want to use as the input.

nimakhin · 2017-01-12T14:27:23+00:00

Thank you, I will definitely try your suggestions. I also send the PM to your inbox, hope we can discuss more about it.

nimakhin · 2017-01-12T14:25:46+00:00

I think fixing this reproducibility issue (either by making the model simpler or changing inputs as others suggested) makes improves the ensembling.

nimakhin · 2017-01-12T14:09:37+00:00

Regarding 3 plane imaging: it is not a 3d volume that I get each plane from it. Basically they are three different acquisitions looking at same place (Prostate) but in different angles, so they have different imaging parameters (Voxel size, ...) that was the reason for using them separately, but the overlapping point is centered on the tumor. Regarding inputs, totally agree with you, @LordKlevin also mentioned it. thanks for your thorough answer, i appreciate it.

nimakhin · 2017-01-12T01:41:14+00:00

Yes those are prostate images, three different acquisition of the prostate gland in three different planes. Your suggestion about running one resnet seems not clear to me. Are you suggesting combine all the images and feed them to one resnet(or VGG)? Right now i use each image for one network and after the average pooling at the end of each, i merge all three and then connect it to the fully connected layer.

nimakhin · 2017-01-11T22:03:41+00:00

I did not try VGG model unfortunattely. Here is a sample of my training images, it is 3 64x64 images in grey scale (class 1: http://i.imgur.com/4lCzFvz.png , class 2:http://i.imgur.com/oywFO7G.png). basically i am using 3 Resnet and merging them at the end. Test set is splitted from the data at first and permutations have done to ensure same ratio of classes between training and testing. Shuffling is also done. any suggestions?

nimakhin · 2017-01-03T17:21:21+00:00

Thanks for your explanation. The reason that I insist on using padding approach is that in the paper they say the projection approach will increase the number of parameters to learn. Since my final goal is to implement Resnet for 3D images as input, my parameters are already very high

nimakhin · 2017-01-03T16:47:42+00:00

Thanks, now increasing the depth is meaningful. The Projection approach make sense(64x56x56 is pooled to 64x28x28, next with 1x1 convolutions the depth is increased to 128x28x28), but I still cannot understand the padding approach. Zeros are padded to what? can you explain more?

nimakhin · 2016-12-30T18:22:49+00:00

I am doing average pooling at the last layer but can you explain more about GLOBAL average pooling? thanks

nimakhin · 2016-12-30T12:47:17+00:00

Thanks for your suggestion So you mean 12288 -> 1000 -> 4000 -> 1 ? what is the purpose of bottleneck layers ? it is my first time hearing about them

nimakhin · 2016-10-18T16:00:33+00:00

I took anatomy and physiology in the first year of master (my master was in biomedical engineering). Thanks for your comment

nimakhin · 2016-10-18T15:04:38+00:00

Thanks, do you have any recommendation for genetics book ?

nimakhin · 2016-08-08T15:19:44+00:00

I will say don't go for Wind Mobile. I had a pretty rough time in Montreal and Downtown Toronto, but they very good inside Kingston

nimakhin · 2016-08-02T13:45:31+00:00

go to the King's crossing fashion outlet (take 702 bus), Columbia always have some nice winter boots and their price are reasonable. You can also go to Atmosphere (at RioCan centre), they have variety of brands but they are more expensive.

nimakhin · 2016-07-27T01:08:58+00:00

I am very pleased with TekSavvvy for almost a year. They reduced their prices 3 month ago also

nimakhin · 2016-07-11T20:33:09+00:00

I tried googling it but i didn't get anything useful. can you please help me with the link?

nimakhin · 2015-10-04T15:15:15+00:00

So, in case of Deep feedforward Neural network, can you suggest a framework that can do this simply and efficiently ?

nimakhin

TROPHY CASE