Simulated Data Based Deep Neural Network Training for Underground Cavity Detection

The Journal of Korean Institute of Communications and Information Sciences ◽

10.7840/kics.2021.46.5.923 ◽

2021 ◽

Vol 46 (5) ◽

pp. 923-927

Author(s):

Youngjun Yoo ◽

Daehee Kim ◽

Myunghak Lee ◽

Jaekoo Lee

Keyword(s):

Neural Network ◽

Deep Neural Network ◽

Simulated Data ◽

Neural Network Training ◽

Underground Cavity ◽

Cavity Detection ◽

Network Training

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A Deep Neural Network Training Architecture with Inference-aware Heterogeneous Data-type

IEEE Transactions on Computers ◽

10.1109/tc.2021.3078316 ◽

2021 ◽

pp. 1-1

Author(s):

Seungkyu Choi ◽

Jaekang Shin ◽

Lee-Sup Kim

Keyword(s):

Neural Network ◽

Deep Neural Network ◽

Heterogeneous Data ◽

Data Type ◽

Neural Network Training ◽

Network Training

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An Energy-Efficient Deep Neural Network Training Processor with Bit-Slice-Level Reconfigurability and Sparsity Exploitation

2021 IEEE Symposium in Low-Power and High-Speed Chips (COOL CHIPS) ◽

10.1109/coolchips52128.2021.9410324 ◽

2021 ◽

Author(s):

Donghyeon Han ◽

Dongseok Im ◽

Gwangtae Park ◽

Youngwoo Kim ◽

Seokchan Song ◽

...

Keyword(s):

Neural Network ◽

Energy Efficient ◽

Deep Neural Network ◽

Neural Network Training ◽

Network Training

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Deep Neural Network Training Accelerator Designs in ASIC and FPGA

2020 International SoC Design Conference (ISOCC) ◽

10.1109/isocc50952.2020.9333063 ◽

2020 ◽

Author(s):

Shreyas K. Venkataramanaiah ◽

Shihui Yin ◽

Yu Cao ◽

Jae-Sun Seo

Keyword(s):

Neural Network ◽

Deep Neural Network ◽

Neural Network Training ◽

Network Training

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Low Complexity Gradient Computation Techniques to Accelerate Deep Neural Network Training

IEEE Transactions on Neural Networks and Learning Systems ◽

10.1109/tnnls.2021.3130991 ◽

2021 ◽

pp. 1-15

Author(s):

Dongyeob Shin ◽

Geonho Kim ◽

Joongho Jo ◽

Jongsun Park

Keyword(s):

Neural Network ◽

Deep Neural Network ◽

Low Complexity ◽

Neural Network Training ◽

Computation Techniques ◽

Network Training ◽

Gradient Computation

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A FeRAM based Volatile/Non-volatile Dual-mode Buffer Memory for Deep Neural Network Training

10.23919/date51398.2021.9474180 ◽

2021 ◽

Author(s):

Yandong Luo ◽

Yuan-Chun Luc ◽

Shimeng Yu

Keyword(s):

Neural Network ◽

Deep Neural Network ◽

Neural Network Training ◽

Dual Mode ◽

Buffer Memory ◽

Network Training

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Exploring one pass learning for deep neural network training with averaged stochastic gradient descent

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ◽

10.1109/icassp.2014.6854928 ◽

2014 ◽

Author(s):

Zhao You ◽

Xiaorui Wang ◽

Bo Xu

Keyword(s):

Neural Network ◽

Gradient Descent ◽

Deep Neural Network ◽

Stochastic Gradient ◽

Stochastic Gradient Descent ◽

Neural Network Training ◽

Network Training

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A 141.4 mW Low-Power Online Deep Neural Network Training Processor for Real-time Object Tracking in Mobile Devices

2018 IEEE International Symposium on Circuits and Systems (ISCAS) ◽

10.1109/iscas.2018.8351398 ◽

2018 ◽

Author(s):

Donghyeon Han ◽

Jinsu Lee ◽

Jinmook Lee ◽

Sungpill Choi ◽

Hoi-Jun Yoo

Keyword(s):

Neural Network ◽

Low Power ◽

Object Tracking ◽

Real Time ◽

Mobile Devices ◽

Deep Neural Network ◽

Neural Network Training ◽

Network Training

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A Unified Coded Deep Neural Network Training Strategy based on Generalized PolyDot codes

2018 IEEE International Symposium on Information Theory (ISIT) ◽

10.1109/isit.2018.8437852 ◽

2018 ◽

Author(s):

Sanghamitra Dutta ◽

Ziqian Bai ◽

Haewon Jeong ◽

Tze Meng Low ◽

Pulkit Grover

Keyword(s):

Neural Network ◽

Deep Neural Network ◽

Neural Network Training ◽

Training Strategy ◽

Network Training

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Communication optimization strategies for distributed deep neural network training: A survey

Journal of Parallel and Distributed Computing ◽

10.1016/j.jpdc.2020.11.005 ◽

2021 ◽

Vol 149 ◽

pp. 52-65 ◽

Author(s):

Shuo Ouyang ◽

Dezun Dong ◽

Yemao Xu ◽

Liquan Xiao

Keyword(s):

Neural Network ◽

Deep Neural Network ◽

Communication Optimization ◽

Neural Network Training ◽

Network Training

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Distributed deep neural network training on edge devices

Proceedings of the 4th ACM/IEEE Symposium on Edge Computing - SEC '19 ◽

10.1145/3318216.3363324 ◽

2019 ◽

Author(s):

Daniel Benditkis ◽

Aviv Keren ◽

Liron Mor-Yosef ◽

Tomer Avidor ◽

Neta Shoham ◽

...

Keyword(s):

Neural Network ◽

Deep Neural Network ◽

Neural Network Training ◽

Network Training

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