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Annachiara Ruospo
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- affiliation: Politecnico di Torino, Turin, Italy
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2020 – today
- 2024
- [c36]Antonio Porsia
, Annachiara Ruospo
Model theft attack against a tinyML application running on an Ultra-Low-Power Open-Source SoC. CF (Companion) 2024 - [c35]V. Turco, Annachiara Ruospo, Ernesto Sánchez, Matteo Sonza Reorda
Early Detection of Permanent Faults in DNNs Through the Application of Tensor-Related Metrics. DDECS 2024: 13-18 - [c34]Dennis Gnad, Martin Gotthard, Jonas Krautter, Angeliki Kritikakou, Vincent Meyers, Paolo Rech, Josie E. Rodriguez Condia, Annachiara Ruospo, Ernesto Sánchez, Fernando Fernandes dos Santos, Olivier Sentieys, Mehdi B. Tahoori, Russell Tessier, Marcello Traiola:
Reliability and Security of AI Hardware. ETS 2024: 1-10 - [c33]Marcello Traiola, Salvatore Pappalardo, Ali Piri, Annachiara Ruospo, Bastien Deveautour, Ernesto Sánchez, Alberto Bosio, Sepide Saeedi, Alessio Carpegna, Anil Bayram Gogebakan, Enrico Magliano, Alessandro Savino
Approximate Fault-Tolerant Neural Network Systems. ETS 2024: 1-10 - [c32]Anil Bayram Gögebakan, Enrico Magliano, Alessio Carpegna, Annachiara Ruospo, Alessandro Savino
SpikingJET: Enhancing Fault Injection for Fully and Convolutional Spiking Neural Networks. IOLTS 2024: 1-7 - [c31]Alberto Bosio, M. Gomes, Fabio Pavanello, A. Porsia
Resiliency Approaches in Convolutional, Photonic, and Spiking Neural Networks. LATS 2024: 1-10 - [i2]Anil Bayram Gogebakan, Enrico Magliano, Alessio Carpegna, Annachiara Ruospo, Alessandro Savino, Stefano Di Carlo:
SpikingJET: Enhancing Fault Injection for Fully and Convolutional Spiking Neural Networks. CoRR abs/2404.00383 (2024) - 2023
- [j4]Annachiara Ruospo
A Survey on Deep Learning Resilience Assessment Methodologies. Computer 56(2): 57-66 (2023) - [c30]Annachiara Ruospo, Gabriele Gavarini, Corrado De Sio, J. Guerrero, Luca Sterpone, Matteo Sonza Reorda
Assessing Convolutional Neural Networks Reliability through Statistical Fault Injections. DATE 2023: 1-6 - [c29]Salvatore Pappalardo, Annachiara Ruospo, Ian O'Connor, Bastien Deveautour, Ernesto Sánchez, Alberto Bosio:
Resilience-Performance Tradeoff Analysis of a Deep Neural Network Accelerator. DDECS 2023: 181-186 - [c28]Gabriele Gavarini, Annachiara Ruospo, Ernesto Sánchez:
On the resilience of representative and novel data formats in CNNs. DFT 2023: 1-6 - [c27]Salvatore Pappalardo, Ali Piri, Annachiara Ruospo, Ian O'Connor, Bastien Deveautour, Ernesto Sánchez, Alberto Bosio:
Investigating the effect of approximate multipliers on the resilience of a systolic array DNN accelerator. DFT 2023: 1-6 - [c26]V. Turco, Annachiara Ruospo, Gabriele Gavarini, Ernesto Sánchez, Matteo Sonza Reorda
Uncovering hidden vulnerabilities in CNNs through evolutionary-based Image Test Libraries. DFT 2023: 1-6 - [c25]Gabriele Gavarini, Annachiara Ruospo, Ernesto Sánchez:
SCI-FI: a Smart, aCcurate and unIntrusive Fault-Injector for Deep Neural Networks. ETS 2023: 1-6 - [c24]Annachiara Ruospo, Gabriele Gavarini, A. Porsia
Image Test Libraries for the on-line self-test of functional units in GPUs running CNNs. ETS 2023: 1-6 - [c23]Gabriele Gavarini, Annachiara Ruospo, Ernesto Sánchez:
Evaluation and Mitigation of Faults Affecting Swin Transformers. IOLTS 2023: 1-7 - [c22]G. Govarini, Annachiara Ruospo, Edgar E. Sánchez:
A Fast Reliability Analysis of Image Segmentation Neural Networks Exploiting Statistical Fault Injections. LATS 2023: 1-6 - [c21]Salvatore Pappalardo, Annachiara Ruospo, Ian O'Connor, Bastien Deveautour, Ernesto Sánchez, Alberto Bosio:
A Fault Injection Framework for AI Hardware Accelerators. LATS 2023: 1-6 - [c20]Mohammad Hasan Ahmadilivani, Mario Barbareschi, Salvatore Barone
Special Session: Approximation and Fault Resiliency of DNN Accelerators. VTS 2023: 1-10 - [i1]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) - 2022
- [j3]Aleksa Damljanovic
Machine learning for hardware security: Classifier-based identification of Trojans in pipelined microprocessors. Appl. Soft Comput. 116: 108068 (2022) - [j2]Lucas Matana Luza
Emulating the Effects of Radiation-Induced Soft-Errors for the Reliability Assessment of Neural Networks. IEEE Trans. Emerg. Top. Comput. 10(4): 1867-1882 (2022) - [c19]Annachiara Ruospo
Selective Hardening of Critical Neurons in Deep Neural Networks. DDECS 2022: 136-141 - [c18]Francesco Angione
Test, Reliability and Functional Safety Trends for Automotive System-on-Chip. ETS 2022: 1-10 - [c17]Gabriele Gavarini, Diego Stucchi, Annachiara Ruospo
Open-Set Recognition: an Inexpensive Strategy to Increase DNN Reliability. IOLTS 2022: 1-7 - [c16]Annachiara Ruospo
Reliability Assessment Methodologies for ANN-based Systems. LATS 2022: 1-4 - 2021
- [j1]Annachiara Ruospo
Investigating data representation for efficient and reliable Convolutional Neural Networks. Microprocess. Microsystems 86: 104318 (2021) - [c15]Lucas Matana Luza
A Model-Based Framework to Assess the Reliability of Safety-Critical Applications. DDECS 2021: 41-44 - [c14]Aleksa Damljanovic, Annachiara Ruospo
A Benchmark Suite of RT-level Hardware Trojans for Pipelined Microprocessor Cores. DDECS 2021: 51-56 - [c13]Annachiara Ruospo
A Suitability Analysis of Software Based Testing Strategies for the On-line Testing of Artificial Neural Networks Applications in Embedded Devices. IOLTS 2021: 1-6 - [c12]Annachiara Ruospo
Pros and Cons of Fault Injection Approaches for the Reliability Assessment of Deep Neural Networks. LATS 2021: 1-5 - 2020
- [c11]Andrea Floridia, Tzamn Melendez Carmona, Davide Piumatti, Annachiara Ruospo
Deterministic Cache-based Execution of On-line Self-Test Routines in Multi-core Automotive System-on-Chips. DATE 2020: 1235-1240 - [c10]Annachiara Ruospo
A Pipelined Multi-Level Fault Injector for Deep Neural Networks. DFT 2020: 1-6 - [c9]Annachiara Ruospo
Evaluating Convolutional Neural Networks Reliability depending on their Data Representation. DSD 2020: 672-679 - [c8]Ckristian Duran, Hanssel Morales
Simulation and Formal: The Best of Both Domains for Instruction Set Verification of RISC-V Based Processors. ISCAS 2020: 1-4 - [c7]Felipe Augusto da Silva
Special Session: AutoSoC - A Suite of Open-Source Automotive SoC Benchmarks. VTS 2020: 1-9
2010 – 2019
- 2019
- [c6]Paolo Bernardi
Non-Intrusive Self-Test Library for Automotive Critical Applications: Constraints and Solutions. DATE 2019: 920-923 - [c5]Annachiara Ruospo
On-line Testing for Autonomous Systems driven by RISC-V Processor Design Verification. DFT 2019: 1-6 - [c4]Andrea Floridia, Davide Piumatti, Annachiara Ruospo
A Decentralized Scheduler for On-line Self-test Routines in Multi-core Automotive System-on-Chips. ITC 2019: 1-10 - [c3]Alberto Bosio, Paolo Bernardi
A Reliability Analysis of a Deep Neural Network. LATS 2019: 1-6 - [c2]Annachiara Ruospo
On the Detection of Always-On Hardware Trojans Supported by a Pre-Silicon Verification Methodology. MTV 2019: 25-30 - 2018
- [c1]Pasquale Davide Schiavone, Ernesto Sánchez, Annachiara Ruospo
An Open-Source Verification Framework for Open-Source Cores: A RISC-V Case Study. VLSI-SoC 2018: 43-48
Coauthor Index
aka: Edgar E. Sánchez
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