Researching | Monocular colony depth extraction algorithms based on transfer learning

Optical Instruments, Volume. 42, Issue 2, 39(2020)

Monocular colony depth extraction algorithms based on transfer learning

Xiangzhou DENG and Rongfu ZHANG^*

Author Affiliations

School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

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References (11)

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Figures & Tables(6)

Fig. 1. Structural diagram of selecting equipment

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Fig. 2. Structural diagram of residual module

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Fig. 3. Deep estimation network structure diagram

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Fig. 4. Colony dataset images

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Fig. 5. Comparison of disparity map effects

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Table 1.
Comparison of experimental results on KITTI dataset
基于KITTI数据集上的实验结果对比

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Table 1.
Comparison of experimental results on KITTI dataset
基于KITTI数据集上的实验结果对比

方法	δ_Rel	δ_RMS	δ_logRMS	t₁	t₂	t₃
Make3D^[14]	0.282	8.734	0.361	0.601	0.820	0.926
Eigen Coarse	0.214	6.563	0.292	0.673	0.884	0.957
Eigen Fine	0.203	6.307	0.282	0.702	0.890	0.958
Laina	0.201	6.471	0.273	0.680	0.898	0.967
Ours	0.171	6.198	0.256	0.764	0.912	0.968

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Xiangzhou DENG, Rongfu ZHANG. Monocular colony depth extraction algorithms based on transfer learning[J]. Optical Instruments, 2020, 42(2): 39

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Paper Information

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Received: Oct. 9, 2019

Accepted: --

Published Online: May. 27, 2020

The Author Email: ZHANG Rongfu (zhangrongfu@usst.edu.cn)

DOI:10.3969/j.issn.1005-5630.2020.02.007

Topics

laser devices and laser physics

Lasers and Laser Optics

laser manufacturing

Instrumentation, Measurement and Metrology