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1
artikkel ajakirjas
AdAM: Adaptive Approximate Multiplier for Fault Tolerance in DNN Accelerators
Taheri, Mahdi
;
Cherezova, Natalia
;
Nazari, Samira
;
Azarpeyvand, Ali
;
Ghasempouri, Tara
;
Daneshtalab, Masoud
;
Raik, Jaan
;
Jenihhin, Maksim
IEEE transactions on device and materials reliability
2024
/
p. 66-75 : ill
https://doi.org//10.1109/TDMR.2024.3523386
artikkel ajakirjas
Seotud publikatsioonid
1
Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine
2
artikkel kogumikus EST
/
artikkel kogumikus ENG
AdAM: adaptive fault-tolerant approximate multiplier for edge DNN accelerators
Taheri, Mahdi
;
Cherezova, Natalia
;
Nazari, Samira
;
Rafiq, Ahsan
;
Azarpeyvand, Ali
;
Ghasempouri, Tara
;
Daneshtalab, Masoud
;
Raik, Jaan
;
Jenihhin, Maksim
2024 IEEE European Test Symposium (ETS): ETS 2024 : May 20-24, 2024, The Hague, Netherlands : proceedings
2024
https://doi.org/10.1109/ETS61313.2024.10567161
Conference Proceedings at Scopus
Article at Scopus
Article at WOS
artikkel kogumikus EST
/
artikkel kogumikus ENG
Seotud publikatsioonid
1
Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine
3
artikkel kogumikus
Challenges in using neural networks in safety-critical applications
Forsberg, H.
;
Linden, Jan
;
Hjorth, J.
;
Manefjord, T.
;
Daneshtalab, Masoud
AIAA/IEEE Digital Avionics Systems Conference - Proceedings,
2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC), Virtual Conference, October 11-16, 2020 : Proceedings
2020
/
7 p
https://doi.org/10.1109/DASC50938.2020.9256519
artikkel kogumikus
4
artikkel kogumikus
Composing graph theory and deep neural networks to evaluate SEU type soft error effects
Balakrishnan, Aneesh
;
Lange, Thomas
;
Glorieux, Maximilien
;
Alexandrescu, Dan
;
Jenihhin, Maksim
9th Mediterranean Conference on Embedded Computing (MECO'2020), Budva, Montenegro, 8-11 June 2020
2020
https://doi.org/10.1109/MECO49872.2020.9134279
artikkel kogumikus
Seotud publikatsioonid
1
A synthetic, hierarchical approach for modelling and managing complex systems' quality and reliability = Sünteetiline, hierarhiline lähenemine keerukate süsteemide kvaliteedi ja töökindluse modelleerimiseks ja haldamiseks
5
artikkel kogumikus EST
/
artikkel kogumikus ENG
Data augmentation and teacher-student training for LF-MMI based robust speech recognition
Ullah, Asad
;
Alumäe, Tanel
Text, Speech, and Dialogue : 21st International Conference, TSD 2018, Brno, Czech Republic, September 11-14, 2018 : proceedings
2018
/
p. 403-410
https://doi.org/10.1007/978-3-030-00794-2_43
Conference Proceedings at Scopus
Article at Scopus
Article at WOS
artikkel kogumikus EST
/
artikkel kogumikus ENG
6
artikkel kogumikus
DeepAxe : a framework for exploration of approximation and reliability trade-offs in DNN accelerators
Taheri, Mahdi
;
Riazati, Mohamad
;
Ahmadilivani, Mohammad Hasan
;
Jenihhin, Maksim
;
Daneshtalab, Masoud
;
Raik, Jaan
;
Sjödin, Mikael
;
Lisper, Björn
2023 24th International Symposium on Quality Electronic Design (ISQED)
2023
/
8 p. : ill
https://doi.org/10.1109/ISQED57927.2023.10129353
artikkel kogumikus
Seotud publikatsioonid
1
Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine
7
artikkel kogumikus
DeepHLS: A complete toolchain for automatic synthesis of deep neural networks to FPGA
Riazati, Mohammad
;
Daneshtalab, Masoud
;
Sjodin, Mikael
;
Lisper, Bjorn
ICECS 2020 - 27th IEEE International Conference on Electronics, Circuits and Systems, November 23-25, 2020, Virtual Conference : Proceedings
2020
/
4 p
https://doi.org/10.1109/ICECS49266.2020.9294881
artikkel kogumikus
8
artikkel kogumikus EST
/
artikkel kogumikus ENG
Exploration of Activation Fault Reliability in Quantized Systolic Array-Based DNN Accelerators
Taheri, Mahdi
;
Cherezova, Natalia
;
Ansari, Mohammad Saeed
;
Jenihhin, Maksim
;
Mahani, Ali
;
Daneshtalab, Masoud
;
Raik, Jaan
25th International Symposium on Quality Electronic Design (ISQED)
2024
/
8 p. : ill
https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10528372
https://doi.org/10.1109/ISQED60706.2024.10528372
Conference proceedings at Scopus
Article at Scopus
Article at WOS
artikkel kogumikus EST
/
artikkel kogumikus ENG
Seotud publikatsioonid
1
Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine
9
artikkel kogumikus EST
/
artikkel kogumikus ENG
FARMUR: fair adversarial retraining to mitigate unfairness in robustness
Mousavi, Seyed Ali
;
Mousavi, Hamid
;
Daneshtalab, Masoud
Advances in Databases and Information Systems: 27th European Conference, ADBIS 2023, Barcelona, Spain, September 4–7, 2023 : proceedings
2023
/
p. 133-145
https://doi.org/10.1007/978-3-031-42914-9_10
Conference proceedings at Scopus
Article at Scopus
artikkel kogumikus EST
/
artikkel kogumikus ENG
10
artikkel kogumikus EST
/
artikkel kogumikus ENG
FORTUNE: A Negative Memory Overhead Hardware-Agnostic Fault TOleRance TechniqUe in DNNs
Nazari, Samira
;
Taheri, Mahdi
;
Azarpeyvand, Ali
;
Afsharchi, Mohsen
;
Ghasempouri, Tara
;
Herglotz, Christian
;
Daneshtalab, Masoud
;
Jenihhin, Maksim
2024 IEEE 33rd Asian Test Symposium (ATS)
2024
/
p. 1-6 : ill
https://doi.org//10.1109/ATS64447.2024.10915463
Conference proceedings at Scopus
Article at Scopus
Article at WOS
artikkel kogumikus EST
/
artikkel kogumikus ENG
Seotud publikatsioonid
1
Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine
11
artikkel kogumikus
Gate-level graph representation learning : a step towards the improved stuck-at faults analysis
Balakrishnan, Aneesh
;
Alexandrescu, Dan
;
Jenihhin, Maksim
;
Lange, Thomas
;
Glorieux, Maximilien
Proceedings of the Twenty Second International Symposium on Quality Electronic Design (ISQED) : Santa Clara, USA, 7-9 April 2021
2021
/
p. 24-30
https://doi.org/10.1109/ISQED51717.2021.9424256
artikkel kogumikus
Seotud publikatsioonid
1
A synthetic, hierarchical approach for modelling and managing complex systems' quality and reliability = Sünteetiline, hierarhiline lähenemine keerukate süsteemide kvaliteedi ja töökindluse modelleerimiseks ja haldamiseks
12
artikkel kogumikus EST
/
artikkel kogumikus ENG
Heterogeneous Approximation of DNN HW Accelerators based on Channels Vulnerability
Cherezova, Natalia
;
Pappalardo, Salvatore
;
Taheri, Mahdi
;
Ahmadilivani, Mohammad Hasan
;
Deveautour, Bastien
;
Bosio, Alberto
;
Raik, Jaan
;
Jenihhin, Maksim
2024 IFIP/IEEE 32nd International Conference on Very Large Scale Integration (VLSI-SoC)
2024
/
4 p. : ill
https://doi.org//10.1109/VLSI-SoC62099.2024.10767798
Conference proceedings at Scopus
Article at Scopus
artikkel kogumikus EST
/
artikkel kogumikus ENG
Seotud publikatsioonid
1
Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine
13
artikkel kogumikus
SAFFIRA: a Framework for Assessing the Reliability of Systolic-Array-Based DNN Accelerators
Taheri, Mahdi
;
Daneshtalab, Masoud
;
Raik, Jaan
;
Jenihhin, Maksim
;
Pappalardo, Salvatore
;
Jimenez, Paul
;
Deveautour, Bastien
;
Bosio, Alberto
2024 27th International Symposium on Design & Diagnostics of Electronic Circuits & Systems (DDECS) : 03-05 April 2024, Kielce, Poland
2024
/
p. 19–24 : ill
https://doi.org//10.1109/DDECS60919.2024.10508925
artikkel kogumikus
Seotud publikatsioonid
1
Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine
14
artikkel kogumikus EST
/
artikkel kogumikus ENG
Special session : approximation and fault resiliency of DNN accelerators
Ahmadilivani, Mohammad Hasan
;
Barbareschi, Mario
;
Barone, Salvatore
;
Bosio, Alberto
;
Daneshtalab, Masoud
;
Torca, Salvatore Della
;
Gavarini, Gabriele
;
Jenihhin, Maksim
;
Raik, Jaan
;
Taheri, Mahdi
2023 IEEE 41st VLSI Test Symposium (VTS) : proceedings
2023
/
10 p. : ill
https://doi.org/10.1109/VTS56346.2023.10140043
Conference proceeding at Scopus
Article at Scopus
Article at WOS
artikkel kogumikus EST
/
artikkel kogumikus ENG
Seotud publikatsioonid
1
Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine
15
artikkel kogumikus EST
/
artikkel kogumikus ENG
Special session: reliability assessment recipes for DNN accelerators
Ahmadilivani, Mohammad Hasan
;
Bosio, Alberto
;
Deveautour, Bastien
;
Dos Santos, Fernando Fernandes
;
Guerrero-Balaguera, Juan-David
;
Jenihhin, Maksim
;
Kritikakou, Angeliki
;
Sierra, Robert Limas
;
Raik, Jaan
;
Taheri, Mahdi
42nd IEEE VLSI Test Symposium, VTS 2024
2024
/
11 p. : ill
https://doi.org/10.1109/VTS60656.2024.10538707
Conference proceedings at Scopus
Article at Scopus
Article at WOS
artikkel kogumikus EST
/
artikkel kogumikus ENG
Seotud publikatsioonid
1
Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine
16
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
A systematic literature review on hardware reliability assessment methods for deep neural networks
Ahmadilivani, Mohammad Hasan
;
Taheri, Mahdi
;
Raik, Jaan
;
Daneshtalab, Masoud
;
Jenihhin, Maksim
ACM Computing Surveys
2024
/
art. 141, 39 p. : ill
https://doi.org/10.1145/3638242
Journal metrics at Scopus
Article at Scopus
Journal metrics at WOS
Article at WOS
artikkel ajakirjas EST
/
artikkel ajakirjas ENG
Seotud publikatsioonid
2
Assessment and Enhancement of Hardware Reliability for Deep Neural Networks = Riistvara töökindluse hindamine ja täiustamine süvanärvivõrkude jaoks
Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine
17
artikkel kogumikus EST
/
artikkel kogumikus ENG
ZED-TTE: Zone embedding and deep neural network based travel time estimation approach
Ounoughi, Chahinez
;
Yeferny, Taoufik
;
Ben Yahia, Sadok
2021 International Joint Conference on Neural Networks (IJCNN) : proceedings
2021
/
10 p
https://doi.org/10.1109/IJCNN52387.2021.9533456
Conference Proceedings at Scopus
Article at Scopus
Article at WOS
artikkel kogumikus EST
/
artikkel kogumikus ENG
Kirjeid leitud 17, kuvan
1 - 17
võtmesõna
191
1.
deep neural networks
2.
deep neural networks (DNNs)
3.
deep convolutional neural network
4.
deep neural network
5.
deep neural network compression
6.
artificial neural networks
7.
artificial neural networks (ANN)
8.
constrained artificial neural networks
9.
Constrained neural networks
10.
convolutional neural networks
11.
convolutional neural networks (CNNa)
12.
Convolutional Neural Networks (CNNs)
13.
Fuzzy neural networks
14.
graph neural networks
15.
multilayer neural networks
16.
neural networks
17.
neural-networks
18.
pre-trained neural networks
19.
recurrent neural networks
20.
recurrent neural networks (RNN)
21.
deep donor-deep acceptor pairs
22.
deep brain stimulation
23.
Deep defects
24.
deep energy levels
25.
deep energy renovation
26.
deep eutectic solvents
27.
deep fake
28.
deep fake recognition
29.
deep habits
30.
deep heat well
31.
deep inference
32.
deep layer
33.
deep learning
34.
deep learning (DL)
35.
deep learning classifier
36.
deep learning method
37.
deep learning methods
38.
deep learning model
39.
deep learning model quantization
40.
deep learning network
41.
deep level
42.
deep level traps
43.
deep levels
44.
deep offshore
45.
deep packet inspection
46.
deep reinforcement learning
47.
Deep reinforcing learning SDN
48.
deep renovation
49.
deep understanding
50.
Deep-learning
51.
deep-learning (DL)
52.
deep-sea mining
53.
embedded deep learning
54.
natural deep eutectic solvents
55.
nZEB deep energy renovation
56.
nZEB deep renovation
57.
artificial neural network
58.
Binarized Neural Network (BNN)
59.
cascaded forward neural network (CFNN)
60.
Convolutional Neural Network
61.
convolutional neural network (CNN)
62.
feedforward neural network (FFNN)
63.
Graph Convolutional Neural Network (GCN)
64.
GraphSAGE (Graph Based Neural Network)
65.
human neural progenitor cells
66.
linear Delta robots neural network based model
67.
neural activity
68.
neural additive model
69.
neural architecture search
70.
neural controller
71.
neural development
72.
neural fuzzy modelling control
73.
neural machine translation
74.
neural net
75.
neural network
76.
neural network architecture search
77.
neural network controller
78.
neural network modelling
79.
neural network predictive controller
80.
neural oscillations
81.
neural processing unit
82.
neural stimulation
83.
Radial Basis Function Neural Network (RBFNN)
84.
recurrent neural network language model
85.
Residual Neural Network
86.
spiking neural network (SNN)
87.
Ternary Neural Network
88.
adaptive networks
89.
ad-hoc sensor networks security
90.
automotive communication networks
91.
Bayesian Belief Networks
92.
Bayesian networks
93.
binary search networks
94.
binary sensor networks
95.
body area networks
96.
body sensor networks
97.
cellular networks
98.
communication networks
99.
complex networks
100.
computer networks
101.
content distribution networks
102.
content-addressable storage networks
103.
convolutional networks
104.
cross-border communication networks
105.
decentralized content-addressable storage (DCAS) networks
106.
developmental networks
107.
diffusion networks
108.
digital twin networks (DTNs)
109.
distribution networks
110.
district heating networks
111.
Dynamic networks
112.
dynamics over networks
113.
ecological networks
114.
economic networks
115.
electric power transmission networks
116.
electrical distribution networks
117.
electrical networks
118.
embedded networks/NoC
119.
gateways (computer networks)
120.
generative adversarial networks
121.
geodetic networks
122.
global production networks
123.
graph attention networks
124.
graph convolutional networks
125.
heating and cooling networks
126.
heating networks
127.
hypar-formed networks
128.
IaaS cloud networks
129.
Impedance-source networks
130.
innovation networks
131.
IP networks
132.
iterative networks
133.
knowledge networks
134.
location-based social networks
135.
logistics networks
136.
Long Short-Term Memory Networks (LSTMs)
137.
low voltage networks
138.
low-voltage networks
139.
lumped parameter networks
140.
marketing networks
141.
metabolic networks and pathways
142.
mobile actuator-sensor networks (MAS-Net)
143.
multilayer networks
144.
NB-IoT networks
145.
networks
146.
networks coding
147.
neuro-fuzzy networks and guided missile
148.
non-terrestrial networks
149.
observational networks
150.
on-body networks (BANs)
151.
Online social networks
152.
Optical fiber networks
153.
optical fibre networks
154.
optical networks
155.
optimized routing approach for critical and emergency networks
156.
optimized routing approach for critical and emergency networks simulations
157.
packet switched networks
158.
partner networks
159.
Passive networks
160.
phantom cellular networks
161.
private networks
162.
production networks
163.
Public safety networks
164.
public safety networks (PSN)
165.
public safety networks (PSNs)
166.
reconfigurable scan networks
167.
regional innovation networks
168.
scale-free networks
169.
sensor networks
170.
small district heating networks
171.
SME networks
172.
social networks
173.
social networks
174.
software defined networks (SDN)
175.
sorting networks
176.
supply networks
177.
transmission networks
178.
unreliable wireless networks
179.
WBANs (wireless body area networks)
180.
wearable wireless networks
181.
wearable wireless networks (WWNs)
182.
weighted networks
183.
wireless ad hoc sensor networks
184.
Wireless Body Area Networks
185.
wireless body area networks (WBANs)
186.
wireless body-to-body networks (BBN)
187.
wireless networks
188.
wireless sensor networks
189.
virtual networks
190.
5G networks
191.
5G networks
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