Convolutional neural network based approach for classification of edible oils using low-field nuclear magnetic resonance

Magnetic Resonance ◽

Convolutional Neural Network ◽

Edible Oils ◽

Low Field ◽

Monitoring the oxidation state evolution of unsaturated fatty acids in four microwave-treated edible oils by low-field nuclear magnetic resonance and 1H nuclear magnetic resonance

LWT ◽

10.1016/j.lwt.2020.110740 ◽

2021 ◽

Vol 138 ◽

pp. 110740

Author(s):

Xiaofei Yang ◽

Zongyuan Han ◽

Tianshuang Xia ◽

Yaping Xu ◽

Zhaoxia Wu

Keyword(s):

Fatty Acids ◽

Magnetic Resonance ◽

Oxidation State ◽

Unsaturated Fatty Acids ◽

Edible Oils ◽

Low Field ◽

1H Nuclear Magnetic Resonance ◽

State Evolution ◽

Decision letter for "Suitability of low‐field nuclear magnetic resonance (LF‐NMR) combining with back propagation artificial neural network (BP‐ANN) to predict printability of polysaccharide hydrogels 3D printing"

10.1111/ijfs.14844/v2/decision1 ◽

2020 ◽

Keyword(s):

Neural Network ◽

Magnetic Resonance ◽

3D Printing ◽

Back Propagation ◽

Low Field ◽

Artificial Neural ◽

Lf Nmr ◽

Decision letter for "Suitability of low‐field nuclear magnetic resonance (LF‐NMR) combining with back propagation artificial neural network (BP‐ANN) to predict printability of polysaccharide hydrogels 3D printing"

10.1111/ijfs.14844/v1/decision1 ◽

2020 ◽

Keyword(s):

Neural Network ◽

Magnetic Resonance ◽

3D Printing ◽

Back Propagation ◽

Low Field ◽

Artificial Neural ◽

Lf Nmr ◽

Suitability of low‐field nuclear magnetic resonance (LF‐NMR) combining with back propagation artificial neural network (BP‐ANN) to predict printability of polysaccharide hydrogels 3D printing

International Journal of Food Science & Technology ◽

10.1111/ijfs.14844 ◽

2020 ◽

Cited By ~ 1

Author(s):

Chaofan Guo ◽

Min Zhang ◽

Huizhi Chen

Keyword(s):

Neural Network ◽

Magnetic Resonance ◽

3D Printing ◽

Back Propagation ◽

Low Field ◽

Artificial Neural ◽

Lf Nmr ◽

Decision letter for "Suitability of low‐field nuclear magnetic resonance (LF‐NMR) combining with back propagation artificial neural network (BP‐ANN) to predict printability of polysaccharide hydrogels 3D printing"

10.1111/ijfs.14844/v3/decision1 ◽

2020 ◽

Keyword(s):

Neural Network ◽

Magnetic Resonance ◽

3D Printing ◽

Back Propagation ◽

Low Field ◽

Artificial Neural ◽

Lf Nmr ◽

Review for "Suitability of low‐field nuclear magnetic resonance (LF‐NMR) combining with back propagation artificial neural network (BP‐ANN) to predict printability of polysaccharide hydrogels 3D printing"

10.1111/ijfs.14844/v1/review2 ◽

2020 ◽

Keyword(s):

Neural Network ◽

Magnetic Resonance ◽

3D Printing ◽

Back Propagation ◽

Low Field ◽

Artificial Neural ◽

Lf Nmr ◽

Review for "Suitability of low‐field nuclear magnetic resonance (LF‐NMR) combining with back propagation artificial neural network (BP‐ANN) to predict printability of polysaccharide hydrogels 3D printing"

10.1111/ijfs.14844/v2/review2 ◽

2020 ◽

Author(s):

Carlos Sabater

Keyword(s):

Neural Network ◽

Magnetic Resonance ◽

3D Printing ◽

Back Propagation ◽

Low Field ◽

Artificial Neural ◽

Lf Nmr ◽

Review for "Suitability of low‐field nuclear magnetic resonance (LF‐NMR) combining with back propagation artificial neural network (BP‐ANN) to predict printability of polysaccharide hydrogels 3D printing"

10.1111/ijfs.14844/v2/review1 ◽

2020 ◽

Keyword(s):

Neural Network ◽

Magnetic Resonance ◽

3D Printing ◽

Back Propagation ◽

Low Field ◽

Artificial Neural ◽

Lf Nmr ◽

Classification of Brazilian honeys by physical and chemical analytical methods and low field nuclear magnetic resonance (LF 1H NMR)

LWT ◽

10.1016/j.lwt.2013.08.004 ◽

2014 ◽

Vol 55 (1) ◽

pp. 90-95 ◽

Cited By ~ 26

Author(s):

Roberta de Oliveira Resende Ribeiro ◽

Eliane Teixeira Mársico ◽

Carla da Silva Carneiro ◽

Maria Lúcia Guerra Monteiro ◽

Carlos Adam Conte Júnior ◽

...

Keyword(s):

Magnetic Resonance ◽

1H Nmr ◽

Analytical Methods ◽

Low Field ◽

Physical And Chemical ◽

Classification of different walnut varieties using low-field nuclear magnetic resonance technology and cluster analysis

International Journal of Agricultural and Biological Engineering ◽

10.25165/j.ijabe.20191206.5064 ◽

2019 ◽

Vol 12 (6) ◽

pp. 116-121

Author(s):

Ping Song ◽

◽

He Gao ◽

Baojun Zhao ◽

Aiguo Zhang ◽

...

Keyword(s):

Cluster Analysis ◽

Magnetic Resonance ◽

Low Field ◽

And Cluster Analysis ◽