Energy-Aware Physical Synthesis of Deep Neural Networks for Edge-AI Applications in Robotics and VLSI Systems
Energy-aware physical synthesis is essential for deploying deep neural networks (DNNs) in edge-AI applications for robotics and VLSI systems, where stringent power, area, and latency constraints prevail. Beyond algorithm-and software-level optimizations such as network compression and compiler techn...
محفوظ في:
| المؤلف الرئيسي: | Arulprakash, Enoch (author) |
|---|---|
| مؤلفون آخرون: | Bostani, Ali (author), Jayanthi, R. (author), Kowsalya, G. (author), Ramalingam, M. (author), Rathi, M. (author), Srilatha, Y. (author) |
| التنسيق: | article |
| منشور في: |
2025
|
| الوصول للمادة أونلاين: | http://hdl.handle.net/11675/14472 https: |
| الوسوم: |
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