A convolutional neural network based complex scene classification framework using transfer deep combined convolutional activations

Shuyun Liu; Hong Wang; Yutong Jiang; Zhonglin Yang; Zhiyang Ma

doi:10.1117/12.2618661

22 July 2022 A convolutional neural network based complex scene classification framework using transfer deep combined convolutional activations

Shuyun Liu, Hong Wang, Yutong Jiang, Zhonglin Yang, Zhiyang Ma

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Proceedings Volume 12277, 2021 International Conference on Optical Instruments and Technology: Optical Systems, Optoelectronic Instruments, Novel Display, and Imaging Technology; 122770E (2022) https://doi.org/10.1117/12.2618661
Event: 2021 International Conference on Optical Instruments and Technology, 2022, Online Only

Abstract

In many scene classification applications, the variety of surface objects, high within-category diversity and between-category similarity carry challenges for the classification Framework. Most of CNN-based classification methods only extract image features from a single network layer, which may cause the completed image information difficult to extract in complex scenes. We propose a novel transfer deep combined convolutional activations (TDCCA) to integrate both the low-level and high-level features. Extensive comparative experiments are conducted on UC Merced database, Aerial Image database and NWPU-RESISC45 database. The results reveal that our proposed TDCCA achieves higher experimental accuracies than other up-to-date popular methods.

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Shuyun Liu, Hong Wang, Yutong Jiang, Zhonglin Yang, and Zhiyang Ma "A convolutional neural network based complex scene classification framework using transfer deep combined convolutional activations", Proc. SPIE 12277, 2021 International Conference on Optical Instruments and Technology: Optical Systems, Optoelectronic Instruments, Novel Display, and Imaging Technology, 122770E (22 July 2022); https://doi.org/10.1117/12.2618661

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KEYWORDS

Databases

Remote sensing

Scene classification

Convolutional neural networks

Feature extraction

Image classification

Network architectures

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