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| == Energy Efficient ANN Hardware Implementation == | | == Energy Efficient ANN Hardware Implementation == |
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| + | {| style="border:2px solid #abd5f5; background:#f1f5fc;" |
| + | | |
| + | {| |
| + | |- valign=top |
| + | | width="100" |'''title''': |
| + | | width="550"|[[Media:Nojehdeh_Parvin_Altun_ANN_Implementation_with_MAC.pdf | Efficient Hardware Implementation of Convolution Layers Using Multiply-Accumulate Blocks]] |
| + | |- valign="top" |
| + | | '''authors''': |
| + | | Mohammadreza Nojehdeh, Sajjad Parvin, and [[Mustafa Altun]] |
| + | |- valign=top |
| + | | '''presented at''': |
| + | | [http://www.eng.ucy.ac.cy/theocharides/isvlsi21/ IEEE Computer Society Annual Symposium on VLSI (ISVLSI)], Tampa, USA, 2021. |
| + | |} |
| + | |
| + | | align=center width="70" | |
| + | <span class="plainlinks"> |
| + | [[File:PDF.png|65px|link=http://www.ecc.itu.edu.tr/images/4/41/Nojehdeh_Parvin_Altun_ANN_Implementation_with_MAC.pdf]]</span> |
| + | <br> |
| + | [[Media:Nojehdeh_Parvin_Altun_ANN_Implementation_with_MAC.pdf | Paper]] |
| + | | align="center" width="70" | |
| + | <span class="plainlinks"> |
| + | |
| + | [[File:PPT.jpg|60px|link=]] |
| + | </span> |
| + | <br> Slides |
| + | |} |
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| + | {| style="border:2px solid #abd5f5; background:#f1f5fc;" |
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| + | {| |
| + | |- valign=top |
| + | | width="100" |'''title''': |
| + | | width="550"|[[Media:Parvin_Altun_Hardware_Aware_ANN_Training.pdf | A Study on Hardware-Aware Training Techniques for Feedforward Artificial Neural Networks]] |
| + | |- valign="top" |
| + | | '''authors''': |
| + | | Sajjad Parvin and [[Mustafa Altun]] |
| + | |- valign=top |
| + | | '''presented at''': |
| + | | [http://www.eng.ucy.ac.cy/theocharides/isvlsi21/ IEEE Computer Society Annual Symposium on VLSI (ISVLSI)], Tampa, USA, 2021. |
| + | |} |
| + | |
| + | | align=center width="70" | |
| + | <span class="plainlinks"> |
| + | [[File:PDF.png|65px|link=http://www.ecc.itu.edu.tr/images/9/95/Parvin_Altun_Hardware_Aware_ANN_Training.pdf]]</span> |
| + | <br> |
| + | [[Media:Parvin_Altun_Hardware_Aware_ANN_Training.pdf | Paper]] |
| + | | align="center" width="70" | |
| + | <span class="plainlinks"> |
| + | |
| + | [[File:PPT.jpg|60px|link=]] |
| + | </span> |
| + | <br> Slides |
| + | |} |
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| {| style="border:2px solid #abd5f5; background:#f1f5fc;" | | {| style="border:2px solid #abd5f5; background:#f1f5fc;" |
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| |- valign=top | | |- valign=top |
| | '''appeared in''': | | | '''appeared in''': |
− | | width="550"| [http://www.springer.com/journal/11664 Journal of Electronic Materials], early access, 2021. | + | | width="550"| [http://www.springer.com/journal/11664 Journal of Electronic Materials], Vol. 50, Issue 4, pp. 2466–2475, 2021. |
| |- valign=top | | |- valign=top |
| | '''presented at''': | | | '''presented at''': |