FTSET-a software tool for fault tolerance evaluation and improvement

Author:

Dias Fernando Morgado,Borralho Rui,Fontes Pedro,Antunes Ana

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. ZOBNN: Zero-Overhead Dependable Design of Binary Neural Networks with Deliberately Quantized Parameters;2024 IEEE 30th International Symposium on On-Line Testing and Robust System Design (IOLTS);2024-07-03

2. Special Session: Fault-Tolerant Deep Learning: A Hierarchical Perspective;2022 IEEE 40th VLSI Test Symposium (VTS);2022-04-25

3. FitAct: Error Resilient Deep Neural Networks via Fine-Grained Post-Trainable Activation Functions;2022 Design, Automation & Test in Europe Conference & Exhibition (DATE);2022-03-14

4. DeepDyve: Dynamic Verification for Deep Neural Networks;Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security;2020-10-30

5. Automated design of error-resilient and hardware-efficient deep neural networks;Neural Computing and Applications;2020-06-10

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