Elliptical kernels in CNN

username: reza_yazdi
cooked: <p>Hi everyone<br>
Our teacher asked me to use the model shown in the image.<br>
We have a 3D representation of the magnetic simulation. True magnetic sequences must be classified. I did a lot of searching but found nothing useful.<br>
I know that each slice has Elliptical kernels and know <a href="https://en.wikipedia.org/wiki/Ellipse" rel="noopener nofollow ugc">elipse formula from wikipedia</a>, as shown in the images below, but I’m not sure how to implement it with CNNs. That’s something I’m not sure about either.<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/0/e/0e8e255e6640863b2d86ed4e897b13f6cbc43805.png" data-download-href="https://discuss.pytorch.org/uploads/default/0e8e255e6640863b2d86ed4e897b13f6cbc43805" title="download - Copy - Copy"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/0/e/0e8e255e6640863b2d86ed4e897b13f6cbc43805_2_690x219.png" alt="download - Copy - Copy" data-base62-sha1="24LejG8K1LhRtTxLutsrN7Xs8lv" width="690" height="219" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/0/e/0e8e255e6640863b2d86ed4e897b13f6cbc43805_2_690x219.png, https://discuss.pytorch.org/uploads/default/original/3X/0/e/0e8e255e6640863b2d86ed4e897b13f6cbc43805.png 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/0/e/0e8e255e6640863b2d86ed4e897b13f6cbc43805.png 2x" data-dominant-color="E7ECEB"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">download - Copy - Copy</span><span class="informations">893×284 67.3 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>
<p>How can I use Elliptical kernels in CNN’s first layers?<br>
Can I use Elliptical kernels as an attention vector, as shown in the image below?<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/1/4/14db0f4587f1dba1b33db009165503dcd2af679f.png" data-download-href="https://discuss.pytorch.org/uploads/default/14db0f4587f1dba1b33db009165503dcd2af679f" title="download"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/1/4/14db0f4587f1dba1b33db009165503dcd2af679f_2_689x177.png" alt="download" data-base62-sha1="2YuSIxu7bgQQ196krgHsI5I6C4v" width="689" height="177" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/1/4/14db0f4587f1dba1b33db009165503dcd2af679f_2_689x177.png, https://discuss.pytorch.org/uploads/default/optimized/3X/1/4/14db0f4587f1dba1b33db009165503dcd2af679f_2_1033x265.png 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/1/4/14db0f4587f1dba1b33db009165503dcd2af679f.png 2x" data-dominant-color="E3E1E3"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">download</span><span class="informations">1106×284 82.7 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div><br>
thank you</p>