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Plant Segmentation by Supervised Machine Learning Methods and Phenotypic Trait Extraction of Soybean Plants Using Deep Convolutional Neural Networks with Transfer Learning

机译：植物分割通过深度卷积神经网络与转移学习的豆豆植物的植物分割和表型特性

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作者
Adams, Jason R.;
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作者单位

The University of Nebraska - Lincoln.;

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授予单位 The University of Nebraska - Lincoln.;
学科
学位 Ph.D.
年度 2020
页码 66 p.
总页数 66
原文格式 PDF
正文语种 eng
中图分类 AAI27739603;
关键词
Image analysis; Machine learning; Plant phenotyping;

机译：图像分析;机器学习;植物表型;
入库时间 2022-08-17 12:00:44

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1. Weakly Supervised Learning with Deep Convolutional Neural Networks for Semantic Segmentation: Understanding Semantic Layout of Images with Minimum Human Supervision [J] . Seunghoon Hong, Suha Kwak, Bohyung Han IEEE Signal Processing Magazine . 2017,第6期

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2. Automatic lung segmentation in CT images using mask R-CNN for mapping the feature extraction in supervised methods of machine learning using transfer learning [J] . Luis Fabricio Souza, Gabriel Holanda, Francisco Hercules Silva, International Journal of Hybrid Intelligent Systems . 2020,第4期

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3. Evaluation of Different Machine Learning Methods and Deep-Learning Convolutional Neural Networks for Landslide Detection [J] . Omid Ghorbanzadeh, Thomas Blaschke, Khalil Gholamnia, Remote Sensing . 2019,第2期

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4. Plant Taxonomy in Hainan Based on Deep Convolutional Neural Network and Transfer Learning [C] . Wei Liu, Wenlong Feng, Mengxing Huang, IEEE International Conference on Trust, Security and Privacy in Computing and Communications . 2020

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Plant Segmentation by Supervised Machine Learning Methods and Phenotypic Trait Extraction of Soybean Plants Using Deep Convolutional Neural Networks with Transfer Learning

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