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ORCIDMohammad Hasan Ahmadilivani
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2020 – today
- 2024
[j1]Mohammad Hasan Ahmadilivani
, Mahdi Taheri, Jaan Raik, Masoud Daneshtalab, Maksim Jenihhin:
A Systematic Literature Review on Hardware Reliability Assessment Methods for Deep Neural Networks. ACM Comput. Surv. 56(6): 141:1-141:39 (2024)- [c12]Mohammad Hasan Ahmadilivani, Seyedhamidreza Mousavi, Jaan Raik, Masoud Daneshtalab, Maksim Jenihhin:
Cost-Effective Fault Tolerance for CNNs Using Parameter Vulnerability Based Hardening and Pruning. IOLTS 2024: 1-7 - [c11]Maksim Jenihhin, Mahdi Taheri, Natalia Cherezova, Mohammad Hasan Ahmadilivani, Hardi Selg, Artur Jutman, Konstantin Shibin, Anton Tsertov, Sergei Devadze, Rama Mounika Kodamanchili, Ahsan Rafiq, Jaan Raik, Masoud Daneshtalab:
Keynote: Cost-Efficient Reliability for Edge-AI Chips. LATS 2024: 1-2 - [c10]Jakob Rostovski, Mohammad Hasan Ahmadilivani, Andrei Krivosei, Alar Kuusik, Muhammad Mahtab Alam:
Real-Time Gait Anomaly Detection Using 1D-CNN and LSTM. NCDHWS (2) 2024: 260-278 - [c9]Mohammad Hasan Ahmadilivani, Alberto Bosio, Bastien Deveautour, Fernando Fernandes dos Santos, Juan-David Guerrero-Balaguera, Maksim Jenihhin, Angeliki Kritikakou, Robert Limas Sierra, Salvatore Pappalardo, Jaan Raik, Josie E. Rodriguez Condia, Matteo Sonza Reorda, Mahdi Taheri, Marcello Traiola:
Special Session: Reliability Assessment Recipes for DNN Accelerators. VTS 2024: 1-11 - [i8]Mohammad Hasan Ahmadilivani, Seyedhamidreza Mousavi, Jaan Raik, Masoud Daneshtalab, Maksim Jenihhin:
Cost-Effective Fault Tolerance for CNNs Using Parameter Vulnerability Based Hardening and Pruning. CoRR abs/2405.10658 (2024) - [i7]Seyedhamidreza Mousavi, Mohammad Hasan Ahmadilivani, Jaan Raik, Maksim Jenihhin, Masoud Daneshtalab:
ProAct: Progressive Training for Hybrid Clipped Activation Function to Enhance Resilience of DNNs. CoRR abs/2406.06313 (2024) - 2023
- [c8]Mohammad Hasan Ahmadilivani, Mahdi Taheri, Jaan Raik, Masoud Daneshtalab, Maksim Jenihhin:
Enhancing Fault Resilience of QNNs by Selective Neuron Splitting. AICAS 2023: 1-5 - [c7]Mahdi Taheri, Mohammad Hasan Ahmadilivani, Maksim Jenihhin, Masoud Daneshtalab, Jaan Raik:
APPRAISER: DNN Fault Resilience Analysis Employing Approximation Errors. DDECS 2023: 124-127 - [c6]Mohammad Hasan Ahmadilivani, Jaan Raik, Masoud Daneshtalab, Alar Kuusik:
Analysis and Improvement of Resilience for Long Short-Term Memory Neural Networks. DFT 2023: 1-4 - [c5]Mohammad Hasan Ahmadilivani, Mahdi Taheri, Jaan Raik, Masoud Daneshtalab, Maksim Jenihhin:
DeepVigor: VulnerabIlity Value RanGes and FactORs for DNNs' Reliability Assessment. ETS 2023: 1-6 - [c4]Iman Dadras, Sakineh Seydi, Mohammad Hasan Ahmadilivani, Jaan Raik, Mostafa E. Salehi:
Fully-Fusible Convolutional Neural Networks for End-to-End Fused Architecture with FPGA Implementation. ICECS 2023: 1-5 - [c3]Mahdi Taheri, Mohammad Riazati, Mohammad Hasan Ahmadilivani, Maksim Jenihhin, Masoud Daneshtalab, Jaan Raik, Mikael Sjödin, Björn Lisper:
DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators. ISQED 2023: 1-8 - [c2]Mohammad Hasan Ahmadilivani, Mario Barbareschi, Salvatore Barone, Alberto Bosio, Masoud Daneshtalab, Salvatore Della Torca, Gabriele Gavarini, Maksim Jenihhin, Jaan Raik, Annachiara Ruospo, Ernesto Sánchez, Mahdi Taheri:
Special Session: Approximation and Fault Resiliency of DNN Accelerators. VTS 2023: 1-10 - [i6]Mohammad Hasan Ahmadilivani, Mahdi Taheri, Jaan Raik, Masoud Daneshtalab, Maksim Jenihhin:
DeepVigor: Vulnerability Value Ranges and Factors for DNNs' Reliability Assessment. CoRR abs/2303.06931 (2023) - [i5]Mahdi Taheri, Mohammad Riazati, Mohammad Hasan Ahmadilivani, Maksim Jenihhin, Masoud Daneshtalab, Jaan Raik, Mikael Sjödin, Björn Lisper:
DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators. CoRR abs/2303.08226 (2023) - [i4]Mohammad Hasan Ahmadilivani, Mahdi Taheri, Jaan Raik, Masoud Daneshtalab, Maksim Jenihhin:
A Systematic Literature Review on Hardware Reliability Assessment Methods for Deep Neural Networks. CoRR abs/2305.05750 (2023) - [i3]Mahdi Taheri, Mohammad Hasan Ahmadilivani, Maksim Jenihhin, Masoud Daneshtalab, Jaan Raik:
APPRAISER: DNN Fault Resilience Analysis Employing Approximation Errors. CoRR abs/2305.19733 (2023) - [i2]Mohammad Hasan Ahmadilivani, Mario Barbareschi, Salvatore Barone, Alberto Bosio, Masoud Daneshtalab, Salvatore Della Torca, Gabriele Gavarini, Maksim Jenihhin, Jaan Raik, Annachiara Ruospo, Ernesto Sánchez, Mahdi Taheri:
Special Session: Approximation and Fault Resiliency of DNN Accelerators. CoRR abs/2306.04645 (2023) - [i1]Mohammad Hasan Ahmadilivani, Mahdi Taheri, Jaan Raik, Masoud Daneshtalab, Maksim Jenihhin:
Enhancing Fault Resilience of QNNs by Selective Neuron Splitting. CoRR abs/2306.09973 (2023) - 2022
- [c1]Iman Dadras, Mohammad Hasan Ahmadilivani, Saoni Banerji, Jaan Raik, Alvo Aabloo:
An Efficient Analog Convolutional Neural Network Hardware Accelerator Enabled by a Novel Memoryless Architecture for Insect-Sized Robots. MOCAST 2022: 1-6
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