Assessment and Enhancement of Hardware Reliability for Deep Neural Networks = Riistvara töökindluse hindamine ja täiustamine süvanärvivõrkude jaoks
author
supervisor
statement of authorship
Mohammad Hasan Ahmadilivani ; [supervisor: Jaan Raik, co-supervisor: Masoud Daneshtalab ; Tallinn University of Technology, School of Information of Technology, Department of Computer Systems]
type of dissertation
doktoritöö
university/scientific institution
Tallinna Tehnikaülikool
location of publication
Tallinn
publisher
year of publication
pages
266 p. : ill
series
Tallinn University of Technology. Doctoral thesis = Tallinna Tehnikaülikool. Doktoritöö ; 19
subject term
subject of form
ISSN
2585-6898
2585-6901 (PDF)
ISBN
978-9916-80-276-2 (PDF)
978-9916-80-275-5
notes
Autori publikatsioonide nimekiri leheküljel 9
Bibliogr. lk. 129-148
Kokkuvõte eesti keeles
Kättesaadav ka võrguteavikuna
Autori CV inglise ja eesti keeles, lk. 263-266
Thesis (Ph.D. in Information and Communication Technologies) : Tallinn University of Technology, 2025
url
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
TalTech department
language
inglise
- Analysis and improvement of resilience for long short-term memory neural networks
- A systematic literature review on hardware reliability assessment methods for deep neural networks
- Cost-effective fault tolerance for CNNs using parameter vulnerability based hardening and pruning
- Zero-memory-overhead clipping-based fault tolerance for LSTM deep neural networks
- Enhancing fault resilience of QNNs by selective neuron splitting
- DeepVigor: VulnerabIlity Value RanGes and FactORs for DNNs’ Reliability Assessment
- DeepVigor+: Scalable and Accurate Semi-Analytical Fault Resilience Analysis for Deep Neural Networks
- ProAct: Progressive Training for Hybrid Clipped Activation Function to Enhance Resilience of DNNs
Ahmadilivani, M.H. Assessment and Enhancement of Hardware Reliability for Deep Neural Networks = Riistvara töökindluse hindamine ja täiustamine süvanärvivõrkude jaoks. Tallinn : TalTech Press, 2025. 266 p. : ill. (Tallinn University of Technology. Doctoral thesis = Tallinna Tehnikaülikool. Doktoritöö ; 19).