Orange3 Image Classification
$begingroup$
Is the attached workflow correct in case of training and testing with different data sets? Is the attached workflow considered "transfer learning" since my images are not related to the images that the network was pre-trained?
image-classification orange orange3 orange3-imageanalytics
edited Oct 8 '18 at 12:16
Stephen Rauch
1,52551330
asked Sep 16 '18 at 8:23
Nickolas PapanikolaouNickolas Papanikolaou
12
$endgroup$
bumped to the homepage by Community♦ 16 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
Is the attached workflow correct in case of training and testing with different data sets? Is the attached workflow considered "transfer learning" since my images are not related to the images that the network was pre-trained?
image-classification orange orange3 orange3-imageanalytics
edited Oct 8 '18 at 12:16
Stephen Rauch
1,52551330
asked Sep 16 '18 at 8:23
Nickolas PapanikolaouNickolas Papanikolaou
12
$endgroup$
bumped to the homepage by Community♦ 16 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
Is the attached workflow correct in case of training and testing with different data sets? Is the attached workflow considered "transfer learning" since my images are not related to the images that the network was pre-trained?
image-classification orange orange3 orange3-imageanalytics
edited Oct 8 '18 at 12:16
Stephen Rauch
1,52551330
asked Sep 16 '18 at 8:23
Nickolas PapanikolaouNickolas Papanikolaou
12
$endgroup$
Is the attached workflow correct in case of training and testing with different data sets? Is the attached workflow considered "transfer learning" since my images are not related to the images that the network was pre-trained?
image-classification orange orange3 orange3-imageanalytics
image-classification orange orange3 orange3-imageanalytics
edited Oct 8 '18 at 12:16
Stephen Rauch
1,52551330
asked Sep 16 '18 at 8:23
Nickolas PapanikolaouNickolas Papanikolaou
12
edited Oct 8 '18 at 12:16
Stephen Rauch
1,52551330
asked Sep 16 '18 at 8:23
Nickolas PapanikolaouNickolas Papanikolaou
12
edited Oct 8 '18 at 12:16
Stephen Rauch
1,52551330
edited Oct 8 '18 at 12:16
Stephen Rauch
1,52551330
edited Oct 8 '18 at 12:16
Stephen Rauch
1,52551330
1,52551330
asked Sep 16 '18 at 8:23
Nickolas PapanikolaouNickolas Papanikolaou
12
asked Sep 16 '18 at 8:23
Nickolas PapanikolaouNickolas Papanikolaou
12
asked Sep 16 '18 at 8:23
Nickolas PapanikolaouNickolas Papanikolaou
12
12
bumped to the homepage by Community♦ 16 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 16 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
Your workflow is correct and you are doing a type of transfer learning where only the last layer is fine-tuned. Image embedding widget calculates features that are the activations of a penultimate layer of Inception-v3, VGG or Painters network. All of those networks are trained on the different set of images. VGG and Inception-v3 are trained on ImageNet dataset and Painters network is trained on the set of artworks. In the transfer learning you are implementing with the workflow you fine-tune all of the connected classifiers for your images.
answered Oct 8 '18 at 11:06
PrimozPrimoz
16818
$endgroup$
add a comment |
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
});
}
});
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%2f38320%2forange3-image-classification%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
Your workflow is correct and you are doing a type of transfer learning where only the last layer is fine-tuned. Image embedding widget calculates features that are the activations of a penultimate layer of Inception-v3, VGG or Painters network. All of those networks are trained on the different set of images. VGG and Inception-v3 are trained on ImageNet dataset and Painters network is trained on the set of artworks. In the transfer learning you are implementing with the workflow you fine-tune all of the connected classifiers for your images.
answered Oct 8 '18 at 11:06
PrimozPrimoz
16818
$endgroup$
add a comment |
$begingroup$
Your workflow is correct and you are doing a type of transfer learning where only the last layer is fine-tuned. Image embedding widget calculates features that are the activations of a penultimate layer of Inception-v3, VGG or Painters network. All of those networks are trained on the different set of images. VGG and Inception-v3 are trained on ImageNet dataset and Painters network is trained on the set of artworks. In the transfer learning you are implementing with the workflow you fine-tune all of the connected classifiers for your images.
answered Oct 8 '18 at 11:06
PrimozPrimoz
16818
$endgroup$
add a comment |
$begingroup$
Your workflow is correct and you are doing a type of transfer learning where only the last layer is fine-tuned. Image embedding widget calculates features that are the activations of a penultimate layer of Inception-v3, VGG or Painters network. All of those networks are trained on the different set of images. VGG and Inception-v3 are trained on ImageNet dataset and Painters network is trained on the set of artworks. In the transfer learning you are implementing with the workflow you fine-tune all of the connected classifiers for your images.
answered Oct 8 '18 at 11:06
PrimozPrimoz
16818
$endgroup$
Your workflow is correct and you are doing a type of transfer learning where only the last layer is fine-tuned. Image embedding widget calculates features that are the activations of a penultimate layer of Inception-v3, VGG or Painters network. All of those networks are trained on the different set of images. VGG and Inception-v3 are trained on ImageNet dataset and Painters network is trained on the set of artworks. In the transfer learning you are implementing with the workflow you fine-tune all of the connected classifiers for your images.
answered Oct 8 '18 at 11:06
PrimozPrimoz
16818
answered Oct 8 '18 at 11:06
PrimozPrimoz
16818
answered Oct 8 '18 at 11:06
PrimozPrimoz
16818
answered Oct 8 '18 at 11:06
PrimozPrimoz
16818
16818
add a comment |
add a comment |
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%2f38320%2forange3-image-classification%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
