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Technical Report: NEMO DNN Quantization for Deployment Model

Technical Report: NEMO DNN Quantization for Deployment Model

13 April 2020
Francesco Conti
    MQ
ArXivPDFHTML

Papers citing "Technical Report: NEMO DNN Quantization for Deployment Model"

5 / 5 papers shown
Title
Utilizing Explainable AI for Quantization and Pruning of Deep Neural
  Networks
Utilizing Explainable AI for Quantization and Pruning of Deep Neural Networks
Muhammad Sabih
Frank Hannig
J. Teich
MQ
80
23
0
20 Aug 2020
Memory-Driven Mixed Low Precision Quantization For Enabling Deep Network
  Inference On Microcontrollers
Memory-Driven Mixed Low Precision Quantization For Enabling Deep Network Inference On Microcontrollers
Manuele Rusci
Alessandro Capotondi
Luca Benini
MQ
58
75
0
30 May 2019
Additive Noise Annealing and Approximation Properties of Quantized
  Neural Networks
Additive Noise Annealing and Approximation Properties of Quantized Neural Networks
Matteo Spallanzani
Lukas Cavigelli
G. P. Leonardi
Marko Bertogna
Luca Benini
32
15
0
24 May 2019
An Open Source and Open Hardware Deep Learning-powered Visual Navigation
  Engine for Autonomous Nano-UAVs
An Open Source and Open Hardware Deep Learning-powered Visual Navigation Engine for Autonomous Nano-UAVs
Daniele Palossi
Francesco Conti
Luca Benini
39
43
0
10 May 2019
PACT: Parameterized Clipping Activation for Quantized Neural Networks
PACT: Parameterized Clipping Activation for Quantized Neural Networks
Jungwook Choi
Zhuo Wang
Swagath Venkataramani
P. Chuang
Vijayalakshmi Srinivasan
K. Gopalakrishnan
MQ
54
945
0
16 May 2018
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