• Laser & Optoelectronics Progress
  • Vol. 58, Issue 4, 0415006 (2021)
Xiaohua Qiu1、2、*, Min Li1、*, Liqiong Zhang1, and Lin Dong2
Author Affiliations
  • 1College of Operational Support, The Rocket Force University of Engineering, Xi'an, Shaanxi 710025, China
  • 2College of Information Engineering, Engineering University of PAP, Xi'an, Shaanxi 710086, China
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    DOI: 10.3788/LOP202158.0415006 Cite this Article Set citation alerts
    Xiaohua Qiu, Min Li, Liqiong Zhang, Lin Dong. Dual-Band Scene Classification Based on Convolutional Features and Bayesian Decision[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0415006 Copy Citation Text show less
    References

    [1] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 60, 84-90(2017).

    [2] Simonyan K, Zisserman A[2020-06-15]. Very deep convolutional networks for large-scale image recognition [2020-06-15].http:∥arxiv., org/abs/1409, 1556.

    [3] Szegedy C, Vanhoucke V, Ioffe S et al. Rethinking the inception architecture for computer vision[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA., 2818-2826(2016).

    [4] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA., 770-778(2016).

    [5] Jiang J H, Feng X A, Liu F et al. Multi-spectral RGB-NIR image classification using double-channel CNN[J]. IEEE Access, 7, 20607-20613(2019).

    [6] Liu F, Shen T S, Ma X X. Convolutional neural network based multi-band ship target recognition with feature fusion[J]. Acta Optica Sinica, 37, 1015002(2017).

    [7] Ding L, Wang Y, Laganière R et al. Convolutional neural networks for multispectral pedestrian detection[J]. Signal Processing: Image Communication, 82, 115764(2020).

    [8] Zhang Q, Huang N C, Yao L et al. RGB-T salient object detection via fusing multi-level CNN features[J]. IEEE Transactions on Image Processing, 29, 3321-3335(2020).

    [9] Zhang X C, Ye P, Peng S Y et al. DSiamMFT: an RGB-T fusion tracking method via dynamic Siamese networks using multi-layer feature fusion[J]. Signal Processing: Image Communication, 84, 115756(2020).

    [10] Xie L, Lee F, Liu L et al. Scene recognition: a comprehensive survey[J]. Pattern Recognition, 102, 107205(2020).

    [11] Brown M, Süsstrunk S. Multi-spectral SIFT for scene category recognition[C]∥CVPR 2011, June 20-25, 2011, Providence, RI, USA., 177-184(2011).

    [12] Salamati N, Larlus D, Csurka G. Combining visible and near-infrared cues for image categorisation[C]∥22nd British Machine Vision Conference (BMVC 2011), August 30-September 1, 2011, Dundee, Scotland., 1-11(2011).

    [13] Xiao Y, Wu J X. Yuan J S. mCENTRIST: a multi-channel feature generation mechanism for scene categorization[J]. IEEE Transactions on Image Processing, 23, 823-836(2014).

    [14] Zhang Q S, Li W, Li L et al. Infrared and visible image fusion classification based on a codebookless model(CLM)[J]. Journal of Beijing University of Chemical Technology (Natural Science Edition), 45, 71-76(2018).

    [15] Ševo I, Avramović A. Multispectral scene recognition based on dual convolutional neural networks[C]∥Proceedings of the 10th International Symposium on Image and Signal Processing and Analysis, September 18-20, 2017, Ljubl, 126-130(2017).

    [16] Peng X S, Li Y X, Wei X et al. RGB-NIR image categorization with prior knowledge transfer[J]. EURASIP Journal on Image and Video Processing, 2018, 1-11(2018).

    [17] Jiang Z T, Qin J Q, Hu S. Multi-spectral scene recognition method based on multi-way convolution neural network[J]. Computer Science, 46, 265-270(2019).

    [18] Yosinski J, Clune J, Bengio Y et al[2020-06-13]. How transferable are features in deep neural networks? [2020-06-13].https:∥arxiv. org/abs/1411. 1792v1..

    [19] Zhao H H, Liu H. Multiple classifiers fusion and CNN feature extraction for handwritten digits recognition[J]. Granular Computing, 5, 411-418(2020).

    [20] Woźniak M, Graña M, Corchado E. A survey of multiple classifier systems as hybrid systems[J]. Information Fusion, 16, 3-17(2014).

    [21] Zeng H, Yang B, Wang X Q et al. RGB-D object recognition using multi-modal deep neural network and DS evidence theory[J]. Sensors, 19, 529(2019).

    [22] Tang C, Ling Y S, Yang H et al. Decision-level fusion detection for infrared and visible spectra based on deep learning[J]. Infrared and Laser Engineering, 48, 456-470(2019).

    [23] Bengio Y, Courville A, Vincent P. Representation learning: a review and new perspectives[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 1798-1828(2013).

    [24] Zeiler M D, Fergus R[2020-06-15]. Visualizing and understanding convolutional networks [2020-06-15].https:∥arxiv., org/abs/1311, 2901.

    [25] Zhou Z H[M]. Machine learning, 229-232(2016).

    [26] Lin H T, Lin C J, Weng R C. A note on Platt's probabilistic outputs for support vector machines[J]. Machine Learning, 68, 267-276(2007).

    Xiaohua Qiu, Min Li, Liqiong Zhang, Lin Dong. Dual-Band Scene Classification Based on Convolutional Features and Bayesian Decision[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0415006
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