Timeline for What is the difference between using dense layers as opposed to convolutional layers in my networks when dealing with images?
Current License: CC BY-SA 4.0
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| Apr 7, 2020 at 1:28 | comment | added | nbro | Hi and welcome to AI SE! This question is indeed a bit unclear. You mention the GAN, but why is it relevant? Are you interested in 1. the structural differences between dense layers and convolutional layers, 2. the functional difference or, 3. both the structural and functional differences? Also, are you interested in some particular context? Again, why do you mention the GAN? What is your goal and why do you want to know the "difference" between the two? | |
| Apr 7, 2020 at 1:25 | history | edited | nbro | CC BY-SA 4.0 |
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| Apr 3, 2020 at 2:05 | review | Close votes | |||
| Apr 23, 2020 at 21:10 | |||||
| Apr 3, 2020 at 1:16 | comment | added | Recessive | In general, conv layers are able to learn spatial relationships more efficiently and to a better degree. The specifics are more complicated. | |
| Apr 3, 2020 at 1:08 | comment | added | user9947 | Difference w.r.t what? Performance, speed, memory, etc etc? I think you should edit it in the question. | |
| Apr 3, 2020 at 1:01 | history | edited | nbro | CC BY-SA 4.0 |
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| Apr 3, 2020 at 1:00 | review | First posts | |||
| Apr 6, 2020 at 18:13 | |||||
| Apr 3, 2020 at 0:56 | history | asked | AJ2796 | CC BY-SA 4.0 |