Timeline for Does the property of equivariance to translation of convolution layers help to learn translation-invariant features? [duplicate]
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| Mar 12, 2020 at 18:45 | history | closed | Sycorax♦ machine-learning Users with the machine-learning badge or a synonym can single-handedly close machine-learning questions as duplicates and reopen them as needed. | Duplicate of What is translation invariance in computer vision and convolutional neural network? | |
| Mar 12, 2020 at 13:35 | review | Close votes | |||
| Mar 12, 2020 at 18:45 | |||||
| Mar 12, 2020 at 13:18 | comment | added | Christabella Irwanto | Does this answer your question? What is translation invariance in computer vision and convolutional neural network? | |
| Mar 1, 2019 at 16:29 | comment | added | EngrStudent | If you think in terms of gradient descent, there is a radius of "climb" to get from initial to converged. The "invariant to translation" means that the magnitude that the coefficients have to change overall isn't different. It just moves coefficients associated with different node/transfer-functions. | |
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| Nov 15, 2017 at 7:11 | history | tweeted | twitter.com/StackStats/status/930694806808023040 | ||
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| May 16, 2017 at 22:05 | answer | added | Cherif | timeline score: 0 | |
| Mar 24, 2017 at 13:51 | answer | added | Chrigi | timeline score: 2 | |
| Oct 5, 2016 at 8:56 | history | edited | kjetil b halvorsen♦ | CC BY-SA 3.0 |
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| Sep 27, 2016 at 17:29 | history | asked | username123 | CC BY-SA 3.0 |