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Disambiguation of "Qiao, Mengjia"

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Exploring multiple crowdsourced data to learn deep convolutional neural networks for road extraction.

, , , , , , , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2021)

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Miao Qiao

Linhan Qiao

Wenchao Qiao

Fei Qiao

Wenbao Qiao

 

Other publications of authors with the same name

Exploiting Hierarchical Features for Crop Yield Prediction Based on 3-D Convolutional Neural Networks and Multikernel Gaussian Process., , , , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2021)Improved Categorical Cross-Entropy Loss for Training Deep Neural Networks with Noisy Labels., , , , , , and . PRCV (4), volume 13022 of Lecture Notes in Computer Science, page 78-89. Springer, (2021)Exploring multiple crowdsourced data to learn deep convolutional neural networks for road extraction., , , , , , , , , and 2 other author(s). Int. J. Appl. Earth Obs. Geoinformation, (2021)Exploring Label Probability Sequence to Robustly Learn Deep Convolutional Neural Networks for Road Extraction With Noisy Datasets., , , , , , , , , and 2 other author(s). IEEE Trans. Geosci. Remote. Sens., (2022)Multi-Scale Attention Network for Building Extraction from High-Resolution Remote Sensing Images., , , , , , , , , and . Sensors, 24 (3): 1010 (February 2024)An improved categorical cross entropy for remote sensing image classification based on noisy labels., , , , , , , , , and 1 other author(s). Expert Syst. Appl., (2022)Object Extraction From Very High-Resolution Images Using a Convolutional Neural Network Based on a Noisy Large-Scale Dataset., , , , , , , , and . IEEE Access, (2019)Research on Coordination of Urbanization and Driving Forces of Urban Agglomeration in China Based on Nighttime Light Data., and . Agro-Geoinformatics, page 1-6. IEEE, (2018)Enhanced contextual representation with deep neural networks for land cover classification based on remote sensing images., , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2022)Crop yield prediction from multi-spectral, multi-temporal remotely sensed imagery using recurrent 3D convolutional neural networks., , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2021)