Using Metaheuristics for Hyper-Parameter Optimization of Convolutional Neural Networks

2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP) ◽

10.1109/mlsp.2018.8516989 ◽

2018 ◽

Author(s):

Victoria Bibaeva

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Parameter Optimization

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Additive Manufacturing Parameter Optimization with Automated Post-printing Flaw Detection Using Convolutional Neural Networks

Springer Proceedings in Materials - Advances in Materials Research ◽

10.1007/978-981-15-8319-3_14 ◽

2021 ◽

pp. 127-135

Author(s):

E. Prakash ◽

M. Subramaniyan ◽

Anna Kalyani Naveen Sankar ◽

Kumaraguru Chandra Kumar

Keyword(s):

Neural Networks ◽

Additive Manufacturing ◽

Convolutional Neural Networks ◽

Parameter Optimization ◽

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Peer Review #1 of "Multi-objective simulated annealing for hyper-parameter optimization in convolutional neural networks (v0.3)"

10.7287/peerj-cs.338v0.3/reviews/1 ◽

2021 ◽

Keyword(s):

Neural Networks ◽

Simulated Annealing ◽

Peer Review ◽

Convolutional Neural Networks ◽

Parameter Optimization ◽

Multi Objective

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Parameter Optimization in Convolutional Neural Networks Using Gradient Descent

Microservices in Big Data Analytics ◽

10.1007/978-981-15-0128-9_8 ◽

2019 ◽

pp. 87-94

Author(s):

Swaleha Zubair ◽

Anjani Kumar Singha

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Parameter Optimization ◽

Gradient Descent

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Peer Review #1 of "Multi-objective simulated annealing for hyper-parameter optimization in convolutional neural networks (v0.1)"

10.7287/peerj-cs.338v0.1/reviews/1 ◽

2021 ◽

Keyword(s):

Neural Networks ◽

Simulated Annealing ◽

Peer Review ◽

Convolutional Neural Networks ◽

Parameter Optimization ◽

Multi Objective

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Peer Review #2 of "Multi-objective simulated annealing for hyper-parameter optimization in convolutional neural networks (v0.2)"

10.7287/peerj-cs.338v0.2/reviews/2 ◽

2021 ◽

Keyword(s):

Neural Networks ◽

Simulated Annealing ◽

Peer Review ◽

Convolutional Neural Networks ◽

Parameter Optimization ◽

Multi Objective

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Peer Review #2 of "Multi-objective simulated annealing for hyper-parameter optimization in convolutional neural networks (v0.3)"

10.7287/peerj-cs.338v0.3/reviews/2 ◽

2021 ◽

Keyword(s):

Neural Networks ◽

Simulated Annealing ◽

Peer Review ◽

Convolutional Neural Networks ◽

Parameter Optimization ◽

Multi Objective

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Peer Review #1 of "Multi-objective simulated annealing for hyper-parameter optimization in convolutional neural networks (v0.2)"

10.7287/peerj-cs.338v0.2/reviews/1 ◽

2021 ◽

Keyword(s):

Neural Networks ◽

Simulated Annealing ◽

Peer Review ◽

Convolutional Neural Networks ◽

Parameter Optimization ◽

Multi Objective

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Peer Review #2 of "Multi-objective simulated annealing for hyper-parameter optimization in convolutional neural networks (v0.1)"

10.7287/peerj-cs.338v0.1/reviews/2 ◽

2021 ◽

Keyword(s):

Neural Networks ◽

Simulated Annealing ◽

Peer Review ◽

Convolutional Neural Networks ◽

Parameter Optimization ◽

Multi Objective

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Evaluation von Bildparametern und eines convolutional neural networks in der FDG-PET/MR/CT zur Prädiktion des Gesamtüberlebens (OS) und des Therapieansprechens bei Patienten mit Melanom unter CIT.

10.1055/s-0040-1703340 ◽

2020 ◽

Author(s):

F Seith ◽

J Vogel ◽

C la Fougère ◽

T Küstner ◽

K Nikolaou ◽

...

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

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Traffic Lights Detection in adverse conditions using Convolutional Neural Networks

10.33107/ubt-ic.2018.75 ◽

2018 ◽

Author(s):

George Symeonidis ◽

Peter P. Groumpos ◽

Evangelos Dermatas

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Traffic Lights ◽

Adverse Conditions

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