CNN strategy in recognizing spinned images
$begingroup$
I wrote my CNN code from scratch with some convolution kernels. But my CNN can't recognize flipped/spinned images correctly when there are only a few convolution kernels (3*3). My convolution kernels change very little during training. Why?
When there are over 10 convolution kernels, my CNN starts to recognize fipped images. So more kernels help. However it also starts to make wrong recognition.
How will the resolution of images affect the result compared to the convolution kernel size? The higher the resolution, the higher the dimension of this fitting problem
cnn image-recognition kernel
asked 19 hours ago
feynmanfeynman
1578
$endgroup$
add a comment |
$begingroup$
I wrote my CNN code from scratch with some convolution kernels. But my CNN can't recognize flipped/spinned images correctly when there are only a few convolution kernels (3*3). My convolution kernels change very little during training. Why?
When there are over 10 convolution kernels, my CNN starts to recognize fipped images. So more kernels help. However it also starts to make wrong recognition.
How will the resolution of images affect the result compared to the convolution kernel size? The higher the resolution, the higher the dimension of this fitting problem
cnn image-recognition kernel
asked 19 hours ago
feynmanfeynman
1578
$endgroup$
1
$begingroup$
I think you should look at capsule networks
$endgroup$
– Alex
15 hours ago
add a comment |
$begingroup$
I wrote my CNN code from scratch with some convolution kernels. But my CNN can't recognize flipped/spinned images correctly when there are only a few convolution kernels (3*3). My convolution kernels change very little during training. Why?
When there are over 10 convolution kernels, my CNN starts to recognize fipped images. So more kernels help. However it also starts to make wrong recognition.
How will the resolution of images affect the result compared to the convolution kernel size? The higher the resolution, the higher the dimension of this fitting problem
cnn image-recognition kernel
asked 19 hours ago
feynmanfeynman
1578
$endgroup$
I wrote my CNN code from scratch with some convolution kernels. But my CNN can't recognize flipped/spinned images correctly when there are only a few convolution kernels (3*3). My convolution kernels change very little during training. Why?
When there are over 10 convolution kernels, my CNN starts to recognize fipped images. So more kernels help. However it also starts to make wrong recognition.
How will the resolution of images affect the result compared to the convolution kernel size? The higher the resolution, the higher the dimension of this fitting problem
cnn image-recognition kernel
cnn image-recognition kernel
asked 19 hours ago
feynmanfeynman
1578
asked 19 hours ago
feynmanfeynman
1578
edited 18 hours ago
feynman
asked 19 hours ago
feynmanfeynman
1578
asked 19 hours ago
feynmanfeynman
1578
asked 19 hours ago
feynmanfeynman
1578
1578
1
$begingroup$
I think you should look at capsule networks
$endgroup$
– Alex
15 hours ago
add a comment |
1
$begingroup$
I think you should look at capsule networks
$endgroup$
– Alex
15 hours ago
1
1
$begingroup$
I think you should look at capsule networks
$endgroup$
– Alex
15 hours ago
$begingroup$
I think you should look at capsule networks
$endgroup$
– Alex
15 hours ago
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
});
}
});
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%2f45793%2fcnn-strategy-in-recognizing-spinned-images%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
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%2f45793%2fcnn-strategy-in-recognizing-spinned-images%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
1
$begingroup$
I think you should look at capsule networks
$endgroup$
– Alex
15 hours ago