Classification of Air-Cured Tobacco Leaf Pests Using Pruning Convolutional Neural Networks and Transfer Learning
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C. S. Marzan and C. R. Ruiz, “Automated tobacco grading using image processing techniques and a convolutional neural network,†Int. J. Mach. Learn. Comput., vol. 9, no. 6, pp. 807–813, 2019, doi: 10.18178/ijmlc.2019.9.6.877.
A. Harjoko, A. Prahara, T. W. Supardi, I. Candradewi, R. Pulungan, and S. Hartati, “Image processing approach for grading tobacco leaf based on color and quality,†Int. J. Smart Sens. Intell. Syst., vol. 12, no. 1, pp. 1–10, 2019, doi: 10.21307/ijssis-2019-010.
D. S. Guru, P. B. Mallikarjuna, S. Manjunath, and M. M. Shenoi, “Machine Vision Based Classification Of Tobacco Leaves For Automatic Harvesting,†Intell. Autom. Soft Comput., vol. 18, no. 5, pp. 581–590, 2012, doi: 10.1080/10798587.2012.10643267.
Y. Sun, H. Q. Wang, Z. Y. Xia, J. H. Ma, and M. Z. Lv, “Tobacco-disease Image Recognition via Multiple-Attention Classification Network,†J. Phys. Conf. Ser., vol. 1584, no. 1, 2020, doi: 10.1088/1742-6596/1584/1/012008.
D. I. Swasono, H. Tjandrasa, and C. Fatichah, “Classification of tobacco leaf pests using VGG16 transfer learning,†Proc. 2019 Int. Conf. Inf. Commun. Technol. Syst. ICTS 2019, pp. 176–181, 2019, doi: 10.1109/ICTS.2019.8850946.
Y. LeCun, L. Bottou, Y. Bengio, P. Haffner, “Gradient-based learning applied to document recognitionâ€, Proc. IEEE 86 (11) (1998) 2278–2324, 1998.
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, A. Rabinovich, “Going deeper with convolutionsâ€, In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1–9, 2015.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep Residual Learning for Image Recognitionâ€, IEEE Conf. Comput. Vis. Pattern Recognit. 770–778 (2016). doi:10.1109/CVPR.2016.90, 2016.
J. Zou, T. Rui, Y. Zhou, C. Yang, and S. Zhang, “Convolutional neural network simplification via feature map pruning,†Comput. Electr. Eng., vol. 70, pp. 950–958, 2018, doi: 10.1016/j.compeleceng.2018.01.036.
G. Li, J. Wang, H. W. Shen, K. Chen, G. Shan, and Z. Lu, “CNNPruner: Pruning convolutional neural networks with visual analytics,†IEEE Trans. Vis. Comput. Graph., vol. 27, no. 2, pp. 1364–1373, 2021, doi: 10.1109/TVCG.2020.3030461.
B. O. Ayinde, T. Inanc, and J. M. Zurada, “Redundant feature pruning for accelerated inference in deep neural networks,†Neural Networks, vol. 118, pp. 148–158, 2019, doi: 10.1016/j.neunet.2019.04.021.
C. Yang et al., “Structured Pruning of Convolutional Neural Networks via L1 Regularization,†IEEE Access, vol. 7, pp. 106385–106394, 2019, doi: 10.1109/ACCESS.2019.2933032.
P. Singh, V. K. Verma, P. Rai, and V. P. Namboodiri, “Acceleration of Deep Convolutional Neural Networks Using Adaptive Filter Pruning,†IEEE J. Sel. Top. Signal Process., vol. 14, no. 4, pp. 838–847, 2020, doi: 10.1109/JSTSP.2020.2992390.
C. Liu and H. Wu, “Channel pruning based on mean gradient for accelerating Convolutional Neural Networks,†Signal Processing, vol. 156, pp. 84–91, 2019, doi: 10.1016/j.sigpro.2018.10.019.
A. H. Ashouri, T. S. Abdelrahman, and A. Dos Remedios, “Retraining-free methods for fast on-the-fly pruning of convolutional neural networks,†Neurocomputing, vol. 370, no. xxxx, pp. 56–69, 2019, doi: 10.1016/j.neucom.2019.08.063.
F. E. Fernandes and G. G. Yen, “Pruning Deep Convolutional Neural Networks Architectures with Evolution Strategy,†Inf. Sci. (Ny)., vol. 552, pp. 29–47, 2021, doi: 10.1016/j.ins.2020.11.009.
S. K. Yeom et al., “Pruning by explaining: A novel criterion for deep neural network pruning,†Pattern Recognit., vol. 115, 2021, doi: 10.1016/j.patcog.2021.107899.
A. Jordao, M. Lie, and W. R. Schwartz, “Discriminative Layer Pruning for Convolutional Neural Networks,†IEEE J. Sel. Top. Signal Process., vol. 14, no. 4, pp. 828–837, 2020, doi: 10.1109/JSTSP.2020.2975987.
F. Tung and G. Mori, “Deep Neural Network Compression by In-Parallel Pruning-Quantization,†IEEE Trans. Pattern Anal. Mach. Intell., vol. 42, no. 3, pp. 568–579, 2020, doi: 10.1109/TPAMI.2018.2886192.
Y. Liang, W. Liu, S. Yi, H. Yang, and Z. He, “Filter pruning-based two-step feature map reconstruction,†Signal, Image Video Process., vol. 15, no. 7, pp. 1555–1563, 2021, doi: 10.1007/s11760-021-01888-4.
C. Qi et al., “An efficient pruning scheme of deep neural networks for Internet of Things applications,†EURASIP J. Adv. Signal Process., vol. 2021, no. 1, 2021, doi: 10.1186/s13634-021-00744-4.
E. Jeczmionek and P. A. Kowalski, “Flattening layer pruning in convolutional neural networks,†Symmetry (Basel)., vol. 13, no. 7, pp. 1–13, 2021, doi: 10.3390/sym13071147.
S. Zhang, G. Wu, J. Gu, and J. Han, “Pruning convolutional neural networks with an attention mechanism for remote sensing image classification,†Electron., vol. 9, no. 8, pp. 1–19, 2020, doi: 10.3390/electronics9081209.
DOI: http://dx.doi.org/10.18517/ijaseit.12.3.15950
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