Convolutional neural network (CNN) is a kind of deep neural network(NN) composed of convolutional computation, which has excellent image feature extraction ability. This paper mainly studies the application of deep learning algorithm based on multi-layer CNN. This paper first introduces the model structure of CNN in detail, and lists the advantages of CNN and the model＇s parameter update method. Then, aiming at the problem of insufficient feature extraction in image recognition, this paper designs a multi-layer CNN structure (Mc-cnn). Multiple single view CNNs are used to train the image input of a certain view respectively, and the learned features are fused. The experimental results can verify the effectiveness and feasibility of the model network designed in this paper for image recognition.

Malik Teekaraman. Deep Learning Algorithm Based on Multi-layer Convolutional Neural Network. International Journal of Neural Network (2022), Vol. 3, Issue 1: 69-75. https://doi.org/10.38007/NN.2022.030106.

[1] Kaur P, Kaur H. Kernel CNN Deep Learning Algorithm To Classify LIVER Disease. International Journal of Engineering and Advanced Technology, 2019, 8(6):2002-2007. https://doi.org/10.35940/ijeat.E7826.088619

[2] Haenssle H A, Fink C, Schneiderbauer R, et al. Man against machine: diagnostic performance of a deep learning CNN for dermoscopic melanoma recognition in comparison to 58 dermatologists. Annals of Oncology, 2018, 29(8):1836-1842.

[3] Luo Y, Fan Y, Chen X. Research on optimization of deep learning algorithm based on CNN. Journal of Physics: Conference Series, 2021, 1848(1):012038 (5pp). https://doi.org/10.1088/1742-6596/1848/1/012038

[4] Shahril R, Saito A, Shimizu A, et al. Bleeding Classification of Enhanced Wireless Capsule Endoscopy Images using Deep CNN. Journal of Information Science and Engineering, 2020, 36(1):91-108.

[5] Reddy A R, Rao A N. An active model for ranging by deep CNN and elephant herding optimization algorithm (DCNN-EHOA) in WSNs. International Journal of Pervasive Computing and Communications, 2021, ahead-of-print (ahead-of-print).

[6] Anjani I A, Pratiwi Y R, Nurhuda S. Implementation of Deep Learning Using CNN Algorithm for Classification Rose Flower. Journal of Physics: Conference Series, 2021, 1842(1):012002 (11pp). https://doi.org/10.1088/1742-6596/1842/1/012002

[7] Putra B, Amirudin R, Marhaenanto B. The Evaluation of Deep Learning Using CNN (CNN) Approach for Identifying Arabica and Robusta Coffee Plants. Journal of Biosystems Engineering, 2022, 47(2):118-129. https://doi.org/10.1007/s42853-022-00136-y

[8] Giovanni, L, F, et al. Lung nodules diagnosis based on evolutionary CNN. Multimedia Tools and Applications, 2017, 76(18):19039–19055. https://doi.org/10.1007/s11042-017-4480-9

[9] Mukilan P, Semunigus W. Human and object detection using Hybrid Deep CNN. Signal, Image and Video Processing, 2022, 16(7):1913-1923. https://doi.org/10.1007/s11760-022-02151-0

[10] Alotaibi G, Awawdeh M, Farook F F, et al. Artificial intelligence (AI) diagnostic tools: utilizing a CNN (CNN) to assess periodontal bone level radiographically—a retrospective study. BMC Oral Health, 2022, 22(1):1-7. https://doi.org/10.1186/s12903-022-02436-3

[11] Gautam A, Singh V. CLR-based deep convolutional spiking NN with validation based stopping for time series classification. Applied Intelligence, 2020, 50(3):830-848. https://doi.org/10.1007/s10489-019-01552-y

[12] Rohan A, Rabah M, Kim S H. CNN-based Real-Time Object Detection and Tracking for Parrot AR Drone 2. IEEE Access, 2019, PP(99):1-1. https://doi.org/10.1109/ACCESS.2019.2919332

[13] Ruchai A N, Kober V I, Dorofeev K A, et al. Classification of Breast Abnormalities Using a Deep CNN and Transfer Learning. Journal of Communications Technology and Electronics, 2021, 66(6):778-783. https://doi.org/10.1134/S1064226921060206

[14] Deepa B G, Senthil S. Predicting invasive ductal carcinoma tissues in whole slide images of breast Cancer by using CNN model and multiple classifiers. Multimedia Tools and Applications, 2022, 81(6):8575-8596. https://doi.org/10.1007/s11042-022-12114-9

[15] Hur T, Kim L, Park D K. Quantum CNN for classical data classification. Quantum Machine Intelligence, 2022, 4(1):1-18. https://doi.org/10.1007/s42484-021-00061-x

[16] Wang Y, Zhang L, Shu X , et al. Feature-sensitive Deep CNN for Multi-instance Breast Cancer Detection. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021, PP(99):1-1.

[17] Cui R, Azuara G, Scalea F, et al. Damage imaging in skin-stringer composite aircraft panel by ultrasonic-guided waves using deep learning with CNN:. Structural Health Monitoring, 2022, 21(3):1123-1138. https://doi.org/10.1177/14759217211023934

[18] Kumari N, Bhatia R. Efficient facial emotion recognition model using deep CNN and modified joint trilateral filter. Soft Computing, 2022, 26(16):7817-7830. https://doi.org/10.1007/s00500-022-06804-7