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2020 – today
- 2024
[j2]Hans Jakob Damsgaard
, Antoine Grenier, Dewant Katare, Zain Taufique, Salar Shakibhamedan, Tiago Troccoli, Georgios Chatzitsompanis, Anil Kanduri, Aleksandr Ometov, Aaron Yi Ding, Nima Taherinejad, Georgios Karakonstantis, Roger F. Woods, Jari Nurmi:
Adaptive approximate computing in edge AI and IoT applications: A review. J. Syst. Archit. 150: 103114 (2024)- [j1]Salar Shakibhamedan, Nima Amirafshar, Ahmad Sedigh Baroughi, Hadi Shahriar Shahhoseini, Nima TaheriNejad:
ACE-CNN: Approximate Carry Disregard Multipliers for Energy-Efficient CNN-Based Image Classification. IEEE Trans. Circuits Syst. I Regul. Pap. 71(5): 2280-2293 (2024) - [c4]Saeed Seyedfaraji, Severin Jager, Salar Shakibhamedan, Asad Aftab, Semeen Rehman:
OPTIMA: Design-Space Exploration of Discharge-Based In-SRAM Computing: Quantifying Energy-Accuracy Trade-offs. DAC 2024: 331:1-331:6 - [c3]Amin Aminifar, Soheil Khooyooz, Anice Jahanjoo, Salar Shakibhamedan, Nima TaheriNejad:
RecogNoise: Machine-Learning-Based Recognition of Noisy Segments in Electrocardiogram Signals. ISCAS 2024: 1-5 - [c2]Salar Shakibhamedan, Amin Aminifar, Luke Vassallo, Nima TaheriNejad:
Harnessing Approximate Computing for Machine Learning. ISVLSI 2024: 585-591 - 2022
- [c1]Nima TaheriNejad, Salar Shakibhamedan:
Energy-aware Adaptive Approximate Computing for Deep Learning Applications. ISVLSI 2022: 328
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