Energy-aware Adaptive Approximate Computing for Deep Learning Applications N TaheriNejad, S Shakibhamedan 2022 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 328-328, 2022 | 5 | 2022 |
EASE: Energy Optimization through Adaptation–A Review of Runtime Energy-Aware Approximate Deep Learning Algorithms S Shakibhamedan, A Aminifar, N Taherinejad, A Jantsch Authorea Preprints, 2024 | 3 | 2024 |
Adaptive approximate computing in edge AI and IoT applications: A review HJ Damsgaard, A Grenier, D Katare, Z Taufique, S Shakibhamedan, ... Journal of Systems Architecture, 103114, 2024 | 2 | 2024 |
ACE-CNN: Approximate Carry Disregard Multipliers for Energy-Efficient CNN-Based Image Classification S Shakibhamedan, N Amirafshar, AS Baroughi, HS Shahhoseini, ... IEEE Transactions on Circuits and Systems I: Regular Papers, 2024 | 2 | 2024 |
Recognoise: Machine-learning-based recognition of noisy segments in electrocardiogram signals A Aminifar, S Khooyooz, A Jahanjoo, S Shakibhamedan, N TaheriNejad 2024 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2024 | 2 | 2024 |
Persian Musical Instrument Recognition System S Shakibhamedan, SK Hashemifard, F Faradji, M Vali First International Conference on New Research Achievements in Electrical …, 2016 | 2 | 2016 |
An Analytical Approach to Enhancing DNN Efficiency and Accuracy Using Approximate Multiplication S Shakibhamedan, A Jahanjoo, A Aminifar, N Amirafshar, N TaheriNejad, ... 2nd Workshop on Advancing Neural Network Training: Computational Efficiency …, 2024 | | 2024 |
Harnessing Approximate Computing for Machine Learning S Shakibhamedan, A Aminifar, L Vassallo, N TaheriNejad | | 2024 |