Unmanned aerial vehicle image biological soil crust recognition based on UNet++

References

• Alexakis, E. B. and C. Armenakis. 2021. “Performance Improvement of Encoder/decoder-Based CNN Architectures for Change Detection from Very High-Resolution Satellite Imagery.” Canadian Journal of Remote Sensing 47 (2): 309–336. doi:https://doi.org/10.1080/07038992.2021.1922880.
   Web of Science ®Google Scholar
• Badrinarayanan, V., A. Kendall, and R. Cipolla. 2017. “SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation.” IEEE Transactions on Pattern Analysis and Machine Intelligence 39 (12): 2481–2495. doi:https://doi.org/10.1109/tpami.2016.2644615.
   PubMed Web of Science ®Google Scholar
• Belnap, J. 2003. “The World at Your Feet: Desert Biological Soil Crusts.” Frontiers in Ecology and the Environment 1 (4): 181–189. doi:https://doi.org/10.2307/3868062.
   Web of Science ®Google Scholar
• Chamizo, S., Y. Cantón, R. Lázaro, A. Solé-Benet, and F. Domingo. 2011. “Crust Composition and Disturbance Drive Infiltration Through Biological Soil Crusts in Semiarid Ecosystems.” Ecosystems (New York, NY) 15 (1): 148–161. doi:https://doi.org/10.1007/s10021-011-9499-6.
   Google Scholar
• Chaurasia, A., E. Culurciello, and Ieee. 2017. “LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation.” Paper presented at the IEEE Visual Communications and Image Processing (VCIP), St, Petersburg, FL, December 10-13.
   Google Scholar
• Chen, J., M. Y. Zhang, L. Wang, H. Shimazaki, and M. Tamura. 2005. “A New Index for Mapping Lichen-Dominated Biological Soil Crusts in Desert Areas.” Remote Sensing of Environment 96 (2): 165–175. doi:https://doi.org/10.1016/j.rse.2005.02.011.
   Web of Science ®Google Scholar
• Chen, F. J., Y. Ding, Z. X. Wu, D. Y. Wu, J. M. Wen, and Ieee. 2018. “An Improved Framework Called du Plus Plus Applied To Brain Tumor Segmentation.” Paper presented at the 15th IEEE International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), Univ Elect Sci & Technol, China, Chengdu, PEOPLES R CHINA, December 14-16.
   Google Scholar
• Chen, L. C., G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille. 2018. “DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected Crfs.” IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (4): 834–848. doi:https://doi.org/10.1109/tpami.2017.2699184.
   PubMed Web of Science ®Google Scholar
• Chen, B. Y., M. Xia, and J. Q. Huang. 2021. “Mfanet: A Multi-Level Feature Aggregation Network for Semantic Segmentation of Land Cover.” Remote Sensing 13 (4). doi:https://doi.org/10.3390/rs13040731.
   Google Scholar
• Du, X. D., Y. H. Cai, S. Wang, L. J. Zhang, and Ieee 2016. “Overview of Deep Learning.” Paper presented at the 31st Youth Academic Annual Conference of Chinese-Association-of-Automation (YAC), Wuhan, Peoples R China, November 11-13.
   Google Scholar
• Gago, J., C. Douthe, R. E. Coopman, P. P. Gallego, M. Ribas-Carbo, J. Flexas, J. Escalona, and H. Medrano. 2015. “Uavs Challenge to Assess Water Stress for Sustainable Agriculture.” Agricultural Water Management 153: 9–19. doi:https://doi.org/10.1016/j.agwat.2015.01.020.
   Web of Science ®Google Scholar
• Grassi, G., E. Di Sciascio, L. A. Grieco, and P. Vecchio. 2006. “New Object-Oriented Segmentation Algorithm Based on the CNN Paradigm.” Ieee Transactions on Circuits and Systems Ii-Express Briefs 53 (4): 259–263. doi:https://doi.org/10.1109/tcsii.2005.859571.
   Google Scholar
• Guerrero, J. M., G. Pajares, M. Montalvo, J. Romeo, and M. Guijarro. 2012. “Support Vector Machines for Crop/weeds Identification in Maize Fields.” Expert Systems with Applications 39 (12): 11149–11155. doi:https://doi.org/10.1016/j.eswa.2012.03.040.
   Web of Science ®Google Scholar
• He, K. M., X. Y. Zhang, S. Q. Ren, J. Sun, and Ieee2016. “Deep Residual Learning for Image Recognition.” Paper presented at the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, June 27-30.
   Google Scholar
• Hengkang, X., Y. Zhang, X. Shao, and N. Liu. 2022. “Soil Nitrogen and Climate Drive the Positive Effect of Biological Soil Crusts on Soil Organic Carbon Sequestration in Drylands: A Meta-Analysis.” The Science of the Total Environment 803. doi:https://doi.org/10.1016/j.scitotenv.2021.150030.
   Google Scholar
• Huang, Y., Y. F. Pi, K. Ma, X. J. Miao, S. C. Fu, H. Chen, H. Wang, et al. 2021. ”Virtual Patient-Specific Quality Assurance of IMRT Using Unet Plus Plus : Classification, Gamma Passing Rates Prediction, and Dose Difference Prediction.” Frontiers in Oncology 11 :8. doi:https://doi.org/10.3389/fonc.2021.700343.
   Google Scholar
• Jeon, H. Y., L. F. Tian, and H. Zhu. 2011. “Robust Crop and Weed Segmentation Under Uncontrolled Outdoor Illumination.” Sensors (Basel) 11 (6): 6270–6283. doi:https://doi.org/10.3390/s110606270.
   PubMed Web of Science ®Google Scholar
• Jung, P., L. Briegel-Williams, A. Simon, A. Thyssen, and B. Büdel. 2018. “Uncovering Biological Soil Crusts: Carbon Content and Structure of Intact Arctic, Antarctic and Alpine Biological Soil Crusts.” Biogeosciences 15 (4): 1149–1160. doi:https://doi.org/10.5194/bg-15-1149-2018.
   Google Scholar
• Liang, Y., K. Tang, Y. Wang, B. Yuan, F. Tan, F. Feng, and H. Liu. 2019. “Hymenobacter Crusticola Sp. Nov., Isolated from Biological Soil Crust.” International Journal of Systematic and Evolutionary Microbiology 69 (2): 547–551. doi:https://doi.org/10.1099/ijsem.0.003196.
   PubMedGoogle Scholar
• Lin, T. Y., P. Dollar, R. Girshick, K. M. He, B. Hariharan, S. Belongie, and Ieee. 2017. “Feature Pyramid Networks for Object Detection.” Paper presented at the 30th IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, July 21-26.
   Google Scholar
• Long, J., E. Shelhamer, T. Darrell, and Ieee. 2015. “Fully Convolutional Networks for Semantic Segmentation.” Paper presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, June 7-12.
   Google Scholar
• Loshchilov, I. and F. Hutter. 2016. ”Sgdr: Stochastic Gradient Descent with Warm Restarts.” arXiv preprint arXiv:1608.03983.
   Google Scholar
• Luo, H. X., S. P. Dai, M. F. Li, E. P. Liu, Q. Zheng, Y. Y. Hu, and X. P. Yi. 2020. “Comparison of Machine Learning Algorithms for Mapping Mango Plantations Based on Gaofen-1 Imagery.” Journal of Integrative Agriculture 19 (11): 2815–2828. doi:https://doi.org/10.1016/s2095-3119(20)63208-7.
   Google Scholar
• Maxim, B., A. Rannen Triki, and M. B. Blaschko. 2018. “The Lovasz-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks.” In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 4413–4421.
   Google Scholar
• Nitze, I., K. Heidler, S. Barth, and G. Grosse. 2021. “Developing and Testing a Deep Learning Approach for Mapping Retrogressive Thaw Slumps.” Remote Sensing 13 (21): 23. doi:https://doi.org/10.3390/rs13214294.
   Google Scholar
• Peng, D. F., Y. J. Zhang, and H. Y. Guan. 2019. “End-To-End Change Detection for High Resolution Satellite Images Using Improved Unet Plus.” Remote Sensing 11 (11): 23. doi:https://doi.org/10.3390/rs11111382.
   Google Scholar
• Pepe-Ranney, C., C. Koechli, R. Potrafka, C. Andam, E. Eggleston, F. Garcia-Pichel, and D. H. Buckley. 2016. “Non-Cyanobacterial Diazotrophs Mediate Dinitrogen Fixation in Biological Soil Crusts During Early Crust Formation.” The ISME Journal 10 (2): 287–298. doi:https://doi.org/10.1038/ismej.2015.106.
   PubMedGoogle Scholar
• Ronneberger, O., P. Fischer, and T. Brox. 2015. “U-Net: Convolutional Networks for Biomedical Image Segmentation.” Paper presented at the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), Munich, Germany, October 5-9.
   Google Scholar
• Szegedy, C., S. Ioffe, V. Vanhoucke, A. A. Alemi, and Aaai. 2017. “Inception-V4, Inception-ResNet and the Impact of Residual Connections on Learning.” Paper presented at the 31st AAAI Conference on Artificial Intelligence, San Francisco, CA, February 4–9.
   Google Scholar
• Tan, M. X. and Q. V. Le. 2019. “EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.” Paper presented at the 36th International Conference on Machine Learning (ICML), Long Beach, CA, June 9-15.
   Google Scholar
• Tatsumi, K., Y. Yamashiki, M. Angel Canales Torres, and C. Leonidas Ramos Taipe. 2015. “Crop Classification of Upland Fields Using Random Forest of Time-Series Landsat 7 ETM+ Data.” Computers and Electronics in Agriculture 115: 171–179. doi:https://doi.org/10.1016/j.compag.2015.05.001.
   Web of Science ®Google Scholar
• Tong, Z. G., Y. X. Li, Y. Z. Li, K. L. Fan, Y. Si, L. He, and Ieee. 2020. New Network Based on UNET Plus Plus and Densenet For Building Extraction from High Resolution Satellite Imagery. Paper presented at the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Electr Network, September-October 2-26.
   Google Scholar
• Tran, D. Q., M. Park, D. Jung, and S. Park. 2020. “Damage-Map Estimation Using UAV Images and Deep Learning Algorithms for Disaster Management System.” Remote Sensing 12 (24): 15. doi:https://doi.org/10.3390/rs12244169.
   Google Scholar
• Warren, S. D., L. L. Clair, L. R. Stark, L. A. Lewis, N. Pombubpa, T. Kurbessoian, J. E. Stajich, and Z. T. Aanderud. 2019. “Reproduction and Dispersal of Biological Soil Crust Organisms.” Frontiers in Ecology and Evolution 7. doi:https://doi.org/10.3389/fevo.2019.00344.
   Google Scholar
• Xie, S. N., R. Girshick, P. Dollar, Z. W. Tu, K. M. He, and Ieee. 2017. “Aggregated Residual Transformations for Deep Neural Networks.” Paper presented at the 30th IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, July 21-26.
   Google Scholar
• Yang, S. S., K. Tang, X. Zhang, J. Wang, X. Wang, F. Feng, and H. Li. 2016. “Spirosoma Soli Sp. Nov., Isolated from Biological Soil Crusts.” International Journal of Systematic and Evolutionary Microbiology 66 (12): 5568–5574. doi:https://doi.org/10.1099/ijsem.0.001558.
   PubMedGoogle Scholar
• Zhao, Y., Q. Zhu, P. Li, L. Zhao, L. Wang, X. Zheng, and H. Ma. 2014. “Effects of Artificially Cultivated Biological Soil Crusts on Soil Nutrients and Biological Activities in the Loess Plateau.” Journal of Arid Land 6 (6): 742–752. doi:https://doi.org/10.1007/s40333-014-0032-6.
   Google Scholar
• Zhao, H. S., J. P. Shi, X. J. Qi, X. G. Wang, J. Y. Jia, and Ieee. 2017. “Pyramid Scene Parsing Network.” Paper presented at the 30th IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, July 21-26.
   Google Scholar
• Zhou, Z. W., M. M. R. Siddiquee, N. Tajbakhsh, and J. M. Liang. 2018. “Unet Plus Plus : A Nested U-Net Architecture for Medical Image Segmentation.” Paper presented at the 4th International Workshop on Deep Learning in Medical Image Analysis (DLMIA)/8th International Workshop on Multimodal Learning for Clinical Decision Support (ML-CDS), Granada, SPAIN, September 20.
   Google Scholar