DSSEMFF: A Depthwise Separable Squeeze-and-excitation Based on Multi-feature Fusion for Image Classification

Author:

Liu Junjun,Zhang Jun

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Instrumentation

Reference29 articles.

1. Yin, S., Zhang, Ye., & Karim, S. (2018). Large Scale Remote Sensing Image Segmentation Based on Fuzzy Region Competition and Gaussian Mixture Model[J]. IEEE Access., 6, 26069–26080.

2. Swathi, R., & Srinivas, A. (2020). An Improved Image Registration Method Using E-SIFT Feature Descriptor with Hybrid Optimization Algorithm[J]. Journal of the Indian Society of Remote Sensing, 48(2), 215–226.

3. Krizhevsky A, Sutskever I, Hinton GE. ImageNet classification with deep convolutional neural networks. Proceedings of the 25th International Conference on Neural Information Processing Systems. Lake Tahoe: Curran Associates, 2012. 1097–1105.

4. Shin, H. C., Roth, H. R., Gao, M., et al. (2016). Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning[J]. IEEE Transactions on Medical Imaging, 35(5), 1285–1298.

5. Yang, X., & Zhang, H. (2020). Art image classification with double kernel squeeze-and-excitation neural network[J]. Journal of Image and Graphics, 25(05), 0967–0976.

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