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深度神經網路系統之強健性與可靠性增強技術(1/3)
Li, Jin-Fu
(PI)
電機工程學系
概覽
指紋
研究成果
(1)
指紋
探索此專案觸及的研究主題。這些標籤是根據基礎獎勵/補助款而產生。共同形成了獨特的指紋。
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Keyphrases
Robustness Enhancement
100%
Three-Dimensional ICs
100%
Enhancement Techniques
100%
Neural Network System
100%
Dynamic Random Access Memory
100%
Deep Neural Network
100%
Reliability Enhancement
100%
Built-in-self-test (BiST)
100%
Inference Engine
75%
Deep Neural Network Inference
75%
Inference Accuracy
75%
Computational Reduction
50%
Reduction Method
50%
Resilience Capability
50%
WideIO
40%
Controller
40%
Soft Fault
25%
Energy Efficiency
25%
Network Redundancy
25%
Hardware Redundancy
25%
Soft Error
25%
Self-resilience
25%
Fault-tolerance Techniques
25%
Engine Fault
25%
Hardware Fault Tolerance
25%
Neural Hardware
25%
Energy Performance
25%
Fault Resilience
25%
Memory Stacking
20%
Through Silicon via
20%
Boundary Scan
20%
Memory Wall
20%
Three-dimensional Dynamics
20%
Post-bond Test
20%
Test Pattern
20%
Control Signal
20%
Three-dimensional (3D)
20%
Test Circuit
20%
Engineering
Neural Network System
100%
Dynamic Random Access Memory
100%
Built-in Self Test
100%
Deep Neural Network
100%
Logic Die
20%
Boundary Scan
20%
Control Signal
20%
Test Circuit
20%
Energy Performance
14%
Energy Conservation
14%
Energy Efficiency
14%
Fits and Tolerances
14%
Soft Error
14%
Computer Science
Deep Neural Network
100%
Inference Engines
42%
Network Inference
42%
Energy Efficiency
14%
Hardware Redundancy
14%
Hardware Fault Tolerance
14%
Soft Error
14%
Energy Performance
14%
Tolerance Technique
14%