论文类

1. Lingfeng Duan#, Zhihao Wang#, Hongfei Chen, Jinyang Fu, Hanzhi Wei, Zedong Geng, Wanneng Yang. CropPainter: An effective and precise tool for trait-to-image crop visualization based on generative adversarial networks. Plant Methods. 2022, 18:138 Mathematics, 2021, 9(12), 1322

2.        Xinyi Wang, WanNeng Yang, Qiucheng Lv, Chenglong Huang, Xiuying Liang, Guoxing Chen, Lizhong Xiong and LingFeng Duan*, Field rice panicle detection and counting based on deep learning, Frontiers in Plant Science, 2022, 13: 966495.

3.        Xiaohang Ma^#, Yongze Wu^#, Jingfang Shen*, Lingfeng Duan * and Ying Liu, ML-LME: A Plant Growth Situation Analysis Model Using the Hierarchical Effect of Fractal Dimension, Mathematics, 2021, 9(12), 1322.

4.        Baoqi Li, Lin Chen, Weinan Sun, Di Wu, Maojun Wang, Yu Yu, Guoxing Chen, Wanneng Yang, Zhongxu Lin, Xianlong Zhang, Lingfeng Duan *, Xiyan Yang *, Phenomics-based GWAS analysis reveals the genetic architecture for drought resistance in cotton, Plant Biotechnology Journal, 2020, 18: 2533-2544.

5.        段凌凤,潘井旭,郭子龙,等.基于深度信念网络的多品种水稻生物量无损检测.农业机械学报，2019,50(11):136-143

6.        Duan Lingfeng, Han Jiwan, Guo Zilong, et al. Novel Digital Features Discriminate Between Drought Resistant and Drought Sensitive Rice Under Controlled and Field Conditions. Frontiers in Plant Science, 2018, 9:492

7.        段凌凤, 熊雄, 刘谦,等. 基于深度全卷积神经网络的大田稻穗分割. 农业工程学报, 2018, 34(12):202-209

8.        Xiong Xiong（#）, Duan Lingfeng（#）, Liu Lingbo, et al. Panicle-SEG: a robust image segmentation method for rice panicles in the field based on deep learning and superpixel optimization. Plant Methods, 2017, 13(1):104

9.        段凌凤, 杨万能（*）. 水稻表型组学研究概况和展望. 生命科学, 2016, 10:1129-1137（中文核心，被引量：0).

10.        Duan Lingfeng（#）, Huang Chenglong , Chen Guoxing ,et al. Determination of rice panicle numbers during heading by multi-angle imaging, The crop journal, 2015, 178(03):211-219

11.    Yang Wanneng（#）, Guo Zilong （#）,  Huang Chenglong（#）,  Duan Lingfeng（#），Chen Guoxing （#）, Jiang Ni , et al.. Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice, Nature Communications, 2014, 5: 5087 doi: 10.1038/ncomms6087

12.    Yang Wanneng （#）, Duan Lingfeng （#）,Chen Guoxing , et al. Plant phenomics and high-throughput phenotyping: accelerating rice functional genomics using multidisciplinary technologies, Current Opinion in Plant Biology, 2013, 16: 180–187

13.     Duan Lingfeng（#）, Yang Wanneng（#）, Huang Chenglong, et al. A novel machine-vision-based facility for the automatic evaluation of yield-related traits in rice. Plant Methods, 2011, 7(1):44

14.     Duan Lingfeng, Yang Wanneng, Bi Kun,  et al. Fast discrimination and counting of filled/unfilled rice spikelets based on bi-modal imaging. Computers & Electronics in Agriculture, 2011, 75(1):196-203

15.     Duan Lingfeng , Huang Chenglong , Chen Guoxing , et al. High-Throughput Estimation of Yield for Individual Rice Plant Using Multi-angle RGB Imaging, Computer and Computing Technologies in Agriculture VIII, 2015,452: 1-12

16.     Duan Lingfeng, Yang Wanneng, Chen Guoxing, et al. Accurate Inference of Rice Biomass Based on Support Vector Machine. International Conference on Computer and Computing Technologies in Agriculture. Springer International Publishing, 2015:356-365.

授权发明专利

1、段凌凤; 杨万能; 叶军立; 周风燃; 熊立仲; 陈国兴; 基于机器视觉的大田水稻卷叶程度测量方法,ZL2017110969759.

2、段凌凤; 杨万能; 叶军立; 周风燃; 熊立仲; 陈国兴; 基于机器视觉的盆栽水稻卷叶程度测量方法，ZL2017110970417.

3、段凌凤; 杨万能; 叶军立; 王康; 熊立仲; 陈国兴; 基于深度学习和超像素分割的大田稻穗分割方法, ZL2017104464441.

4、段凌凤;杨万能;冯慧;黄成龙;叶军立;熊立仲;陈国兴;周风燃;杨万里;基于深度学习的大田稻穗分割方法，ZL2018110601116

5、段凌凤；杨万能；叶军立；冯慧；黄成龙；周风燃；熊立仲；陈国兴；基于图像分析的多品种全生育期棉花生物量无损测量方法，ZL201810193243X

6、段凌凤,杨万能, 叶军立, 冯慧, 黄成龙,周风燃, 熊立仲, 陈国兴. 基于深度全卷积神经网络的大田稻穗快速分割方法，2018101440011，专利授权日：2022-12-2