Determining the Stir-Frying Degree of Gardeniae Fructus Praeparatus Based on Deep Learning and Transfer Learning
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Acquisition
2.2. Neural Network Structure
2.2.1. VGG16
2.2.2. GoogLeNet
2.2.3. ResNet
2.2.4. MobileNetV2 and MobileNetV3
2.3. Training Strategies
3. Results and Discussion
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Stage | Number | |
---|---|---|
Original Database | Expanded Database | |
C1 | 288 | 1031 |
C2 | 288 | 1010 |
C3 | 288 | 1036 |
C4 | 288 | 1005 |
C5 | 288 | 1008 |
C6 | 144 | 1019 |
C7 | 144 | 1042 |
C8 | 144 | 1013 |
Total | 1872 | 8164 |
Models | Accuracy (%) | Precision (%) | Recall (%) | F1-score (%) | Params (Millions) | Model Size (MB) | Flops (MB) |
---|---|---|---|---|---|---|---|
MobileNetV3 | 98.77 | 98.80 | 98.78 | 98.78 | 1.53 | 16.19 | 58.79 |
MobileNetV2 | 97.66 | 97.73 | 97.67 | 97.68 | 2.23 | 74.25 | 318.97 |
ResNet34 | 97.29 | 97.32 | 97.29 | 97.30 | 21.29 | 37.61 | 36,700 |
VGG16 | 95.82 | 96.04 | 95.83 | 95.86 | 134.29 | 109.29 | 155,000 |
GoogLeNet | 97.42 | 97.50 | 97.42 | 97.42 | 5.98 | 30.03 | 15,900 |
C1 | C2 | C3 | C4 | C5 | C6 | C7 | C8 | |
---|---|---|---|---|---|---|---|---|
R (%) | 99.02 | 98.02 | 97.09 | 100 | 100 | 98.02 | 99.04 | 99.02 |
P (%) | 98.06 | 99.00 | 99.01 | 100 | 99.01 | 100 | 98.10 | 100 |
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Zhang, Y.; Wang, C.; Wang, Y.; Cheng, P. Determining the Stir-Frying Degree of Gardeniae Fructus Praeparatus Based on Deep Learning and Transfer Learning. Sensors 2022, 22, 8091. https://doi.org/10.3390/s22218091
Zhang Y, Wang C, Wang Y, Cheng P. Determining the Stir-Frying Degree of Gardeniae Fructus Praeparatus Based on Deep Learning and Transfer Learning. Sensors. 2022; 22(21):8091. https://doi.org/10.3390/s22218091
Chicago/Turabian StyleZhang, Yuzhen, Chongyang Wang, Yun Wang, and Pengle Cheng. 2022. "Determining the Stir-Frying Degree of Gardeniae Fructus Praeparatus Based on Deep Learning and Transfer Learning" Sensors 22, no. 21: 8091. https://doi.org/10.3390/s22218091
APA StyleZhang, Y., Wang, C., Wang, Y., & Cheng, P. (2022). Determining the Stir-Frying Degree of Gardeniae Fructus Praeparatus Based on Deep Learning and Transfer Learning. Sensors, 22(21), 8091. https://doi.org/10.3390/s22218091