Very Large 3D Input Size to Convolutional NetworkDeconvolutional Network in Semantic SegmentationFully Convolutional Network: How ToHow does a convolutional ply differ from an ordinary convolutional network?Neural network training with known erroneous dataConvolutional neural network fast fourier transformBatching in Recurrent Neural Networks (RNNs) when there is only a single instance per time step?Breaking captcha with a neural network - Learning deep learningChanging the shape of the input layer in tensorflowExtracting Useful features from large convolutional layersInput explanatory categorical variables along with time series into neural network
Pre-mixing cryogenic fuels and using only one fuel tank
How to convince somebody that he is fit for something else, but not this job?
Taxes on Dividends in a Roth IRA
Temporarily disable WLAN internet access for children, but allow it for adults
Find the next value of this number series
How do I tell my boss that I'm quitting soon, especially given that a colleague just left this week
US tourist/student visa
"It doesn't matter" or "it won't matter"?
Non-trope happy ending?
Will the Sticky MAC access policy prevent unauthorized hubs from connecting to a network?
What (the heck) is a Super Worm Equinox Moon?
Is it ethical to recieve stipend after publishing enough papers?
Is there a nicer/politer/more positive alternative for "negates"?
What does Apple's new App Store requirement mean
Has any country ever had 2 former presidents in jail simultaneously?
Why do ¬, ∀ and ∃ have the same precedence?
How do I fix the group tension caused by my character stealing and possibly killing without provocation?
What kind of floor tile is this?
A variation to the phrase "hanging over my shoulders"
Biological Blimps: Propulsion
What are some good ways to treat frozen vegetables such that they behave like fresh vegetables when stir frying them?
awk assign to multiple variables at once
Confused about Cramer-Rao lower bound and CLT
Mimic lecturing on blackboard, facing audience
Very Large 3D Input Size to Convolutional Network
Deconvolutional Network in Semantic SegmentationFully Convolutional Network: How ToHow does a convolutional ply differ from an ordinary convolutional network?Neural network training with known erroneous dataConvolutional neural network fast fourier transformBatching in Recurrent Neural Networks (RNNs) when there is only a single instance per time step?Breaking captcha with a neural network - Learning deep learningChanging the shape of the input layer in tensorflowExtracting Useful features from large convolutional layersInput explanatory categorical variables along with time series into neural network
$begingroup$
I would like to use a 3D convolutional network on a 2000x2000x2000 volume for segmentation. I know I can break the volume into chunks that can fit in VRAM, but I was wondering if there was a way to analyze the entire 3D volume at once.
neural-network
asked yesterday
AlbertAlbert
1
New contributor
Albert is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I would like to use a 3D convolutional network on a 2000x2000x2000 volume for segmentation. I know I can break the volume into chunks that can fit in VRAM, but I was wondering if there was a way to analyze the entire 3D volume at once.
neural-network
asked yesterday
AlbertAlbert
1
New contributor
Albert is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
$begingroup$
Do you actually need such a resolution? Maybe you could downsample your inputs. I would not start with the best resolution possibel.
$endgroup$
– MachineLearner
yesterday
$begingroup$
I do require this resolution because the objects can be very small (such as a 1 voxel wide segmentation).
$endgroup$
– Albert
yesterday
add a comment |
$begingroup$
I would like to use a 3D convolutional network on a 2000x2000x2000 volume for segmentation. I know I can break the volume into chunks that can fit in VRAM, but I was wondering if there was a way to analyze the entire 3D volume at once.
neural-network
asked yesterday
AlbertAlbert
1
New contributor
Albert is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I would like to use a 3D convolutional network on a 2000x2000x2000 volume for segmentation. I know I can break the volume into chunks that can fit in VRAM, but I was wondering if there was a way to analyze the entire 3D volume at once.
neural-network
neural-network
asked yesterday
AlbertAlbert
1
New contributor
Albert is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked yesterday
AlbertAlbert
1
New contributor
Albert is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked yesterday
AlbertAlbert
1
New contributor
Albert is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked yesterday
AlbertAlbert
1
asked yesterday
AlbertAlbert
1
1
New contributor
Albert is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Albert is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Albert is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$begingroup$
Do you actually need such a resolution? Maybe you could downsample your inputs. I would not start with the best resolution possibel.
$endgroup$
– MachineLearner
yesterday
$begingroup$
I do require this resolution because the objects can be very small (such as a 1 voxel wide segmentation).
$endgroup$
– Albert
yesterday
add a comment |
$begingroup$
Do you actually need such a resolution? Maybe you could downsample your inputs. I would not start with the best resolution possibel.
$endgroup$
– MachineLearner
yesterday
$begingroup$
I do require this resolution because the objects can be very small (such as a 1 voxel wide segmentation).
$endgroup$
– Albert
yesterday
$begingroup$
Do you actually need such a resolution? Maybe you could downsample your inputs. I would not start with the best resolution possibel.
$endgroup$
– MachineLearner
yesterday
$begingroup$
Do you actually need such a resolution? Maybe you could downsample your inputs. I would not start with the best resolution possibel.
$endgroup$
– MachineLearner
yesterday
$begingroup$
I do require this resolution because the objects can be very small (such as a 1 voxel wide segmentation).
$endgroup$
– Albert
yesterday
$begingroup$
I do require this resolution because the objects can be very small (such as a 1 voxel wide segmentation).
$endgroup$
– Albert
yesterday
add a comment |
0
active
oldest
votes
Your Answer
StackExchange.ifUsing("editor", function ()
return StackExchange.using("mathjaxEditing", function ()
StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix)
StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
);
);
, "mathjax-editing");
StackExchange.ready(function()
var channelOptions =
tags: "".split(" "),
id: "557"
;
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function()
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled)
StackExchange.using("snippets", function()
createEditor();
);
else
createEditor();
);
function createEditor()
StackExchange.prepareEditor(
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: false,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: null,
bindNavPrevention: true,
postfix: "",
imageUploader:
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
,
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
);
);
Albert is a new contributor. Be nice, and check out our Code of Conduct.
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function ()
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f47692%2fvery-large-3d-input-size-to-convolutional-network%23new-answer', 'question_page');
);
Post as a guest
Required, but never shown
0
active
oldest
votes
0
active
oldest
votes
active
oldest
votes
active
oldest
votes
Albert is a new contributor. Be nice, and check out our Code of Conduct.
Albert is a new contributor. Be nice, and check out our Code of Conduct.
Albert is a new contributor. Be nice, and check out our Code of Conduct.
Albert is a new contributor. Be nice, and check out our Code of Conduct.
Thanks for contributing an answer to Data Science Stack Exchange!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
Use MathJax to format equations. MathJax reference.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function ()
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f47692%2fvery-large-3d-input-size-to-convolutional-network%23new-answer', 'question_page');
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
$begingroup$
Do you actually need such a resolution? Maybe you could downsample your inputs. I would not start with the best resolution possibel.
$endgroup$
– MachineLearner
yesterday
$begingroup$
I do require this resolution because the objects can be very small (such as a 1 voxel wide segmentation).
$endgroup$
– Albert
yesterday