• Optics and Precision Engineering
  • Vol. 28, Issue 12, 2684 (2020)
LIAO Yi-peng11,*, CHEN Shi-yuan1, YANG Jie-jie1, WANG Zhi-gang2, and WANG Wei-xing1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10. 37188/ope. 20202812. 2684 Cite this Article
    LIAO Yi-peng1, CHEN Shi-yuan, YANG Jie-jie, WANG Zhi-gang, WANG Wei-xing. D osin g statu s id en tification an d froth flow featu re extraction based on im proved O R B in N SST dom ain[J]. Optics and Precision Engineering, 2020, 28(12): 2684 Copy Citation Text show less
    References

    [1] ZHANG J, TANG Z H, AI M X, et al.. Nonlinear modeling of the relationship between reagent dosage and flotation froth surface image by Hammerstein-Wiener model[J]. Minerals Engineering, 2018, 120(5): 19-28.

    [2] AI M X, XIE Y F, XIE S W, et al.. Shape-weight. ed bubble size distribution based reagent predictive control for the antimony flotation process[J]. Che. mometrics & Intelligent Laboratory Systems, 2019, 192(8): 103821.

    [3] TANG Z H, TANG L Y, ZHANG G Y, et al.. In. telligent setting method of reagent dosage based on time series froth image in zinc flotation process[J]. Processes, 2020, 8(536): 8050536.

    [4] LI Z M, GUI W H, ZHU J Y. Fault detection in flotation processes based on deep learning and sup. port vector machine[J]. Journal of Central South University, 2019, 26(9): 2504-2515.

    [5] CAO B F, XIE Y F, GUI W H, et al.. Coordinated optimization setting of reagent dosages in roughing-scavenging process of antimony flotation[J]. Journal of Central South University, 2018, 25(1): 95-106.

    [7] WANG Y L, SUN B, ZHANG R Q, et al.. Sul. fur flotation performance recognition based on hierar. chical classification of local dynamic and static froth features[J]. IEEE Access, 2018, 6(3): 14019-14029.

    [8] NAKHAEI F, IRANNAJAD M, MOHAMMAD. NEJAD S. Evaluation of column flotation froth be. havior by image analysis: effects of operational fac. tors in desulfurization of iron ore concentrate[J]. En. ergy Sources, Part A: Recovery, Utilization, and En. vironmental Effects, 2018, 40(19): 2286-2306.

    [9] NAKHAEI F, IRANNAJAD M, MOHAMMAD. NEJAD S. Column flotation performance predic. tion: PCA, ANN and image analysis-based ap. proaches[J]. Physicochemical Problems of Mineral Processing, 2019, 55(5): 1298-1310.

    [10] RUBLEE E, RABAUND V, KONOLIGE K, et al.. ORB: An efficientalternative to SIFT or SURF[C]. Int Conf on Computer Vision. Barcelo. na: IEEE, 2011: 2564-2571.

    [11] GANASALA P, PRASAD A D. Contrast en. hanced multi sensor image fusion based on guided image filter and NSST[J]. IEEE Sensors Journal, 2020, 20(2): 339-346.

    [13] DONG Q, LIU JH, WANG C, et al.. Image mosaic algorithm based on improved BRISK[J]. Journal of Electronics& Information Technology, 2017, 39(2): 444-450.

    [15] SONG J L, YANG J H, LIU F J, et al.. High temperature strain measurement method by combin. ing digital image correlation of laser speckle and im. proved RANSAC smoothing algorithm[J]. Optics and Lasers in Engineering, 2018, 111: 8-18.

    [18] CHENG Y S, ZHAO D W, WANG Y B, et al.. Multi-label learning with kernel extreme learning machine autoencoder[J]. Knowledge-Based Sys. tems, 2019, 178: 1-10.

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    LIAO Yi-peng1, CHEN Shi-yuan, YANG Jie-jie, WANG Zhi-gang, WANG Wei-xing. D osin g statu s id en tification an d froth flow featu re extraction based on im proved O R B in N SST dom ain[J]. Optics and Precision Engineering, 2020, 28(12): 2684
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