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[1] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[2] Hervé Goëau,et al. Overview of LifeCLEF Plant Identification task 2020 , 2020, CLEF.
[3] Anders Krogh Mortensen,et al. The GrassClover Image Dataset for Semantic and Hierarchical Species Understanding in Agriculture , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[4] Julio Saez-Rodriguez,et al. Crowdsourcing Network Inference: The DREAM Predictive Signaling Network Challenge , 2011, Science Signaling.
[5] David P. Anderson,et al. Status of the UC-Berkeley SETI efforts , 2011, Optical Engineering + Applications.
[6] F. Baret,et al. Global Wheat Head Detection (GWHD) Dataset: A Large and Diverse Dataset of High-Resolution RGB-Labelled Images to Develop and Benchmark Wheat Head Detection Methods , 2020, Plant phenomics.
[7] Hong-Yuan Mark Liao,et al. YOLOv4: Optimal Speed and Accuracy of Object Detection , 2020, ArXiv.
[8] Hanno Scharr,et al. Leaf segmentation in plant phenotyping: a collation study , 2016, Machine Vision and Applications.
[9] Seong Joon Oh,et al. CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Features , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[10] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[11] J. Dunning. The elephant in the room. , 2013, European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery.
[12] Aaron Bauer,et al. De novo protein design by citizen scientists , 2019, Nature.
[13] Huiji Gao,et al. Harnessing the Crowdsourcing Power of Social Media for Disaster Relief , 2011, IEEE Intelligent Systems.
[14] Li Wang,et al. Deep Learning for Practical Image Recognition: Case Study on Kaggle Competitions , 2018, KDD.
[15] R. Solovyev,et al. Weighted Boxes Fusion: ensembling boxes for object detection models , 2019, ArXiv.
[16] Hao Lu,et al. TasselNetv2: in-field counting of wheat spikes with context-augmented local regression networks , 2019, Plant Methods.
[17] Dong-Hyun Lee,et al. Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks , 2013 .
[18] Percy Liang,et al. Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization , 2019, ArXiv.
[19] Jure Leskovec,et al. WILDS: A Benchmark of in-the-Wild Distribution Shifts , 2021, ICML.
[20] Hanno Scharr,et al. Finely-grained annotated datasets for image-based plant phenotyping , 2016, Pattern Recognit. Lett..
[21] Kai Zhang,et al. The Plant Pathology Challenge 2020 data set to classify foliar disease of apples , 2020, Applications in plant sciences.
[22] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.
[23] Quoc V. Le,et al. EfficientDet: Scalable and Efficient Object Detection , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Yunchao Wei,et al. Agriculture-Vision: A Large Aerial Image Database for Agricultural Pattern Analysis , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Rasmus Nyholm Jørgensen,et al. A Public Image Database for Benchmark of Plant Seedling Classification Algorithms , 2017, ArXiv.
[26] M. Bethge,et al. Shortcut learning in deep neural networks , 2020, Nature Machine Intelligence.
[27] Hanno Scharr,et al. Citizen crowds and experts: observer variability in image-based plant phenotyping , 2018, Plant Methods.
[28] Kevin Crowston,et al. From Conservation to Crowdsourcing: A Typology of Citizen Science , 2011, 2011 44th Hawaii International Conference on System Sciences.
[29] Hanno Scharr,et al. Sharing the Right Data Right: A Symbiosis with Machine Learning. , 2019, Trends in plant science.
[30] Pierre Bonnet,et al. Overview of LifeCLEF Plant Identification Task 2019: diving into Data Deficient Tropical Countries , 2019, CLEF.
[31] Plant detection and counting from high-resolution RGB images acquired from UAVs: comparison between deep-learning and handcrafted methods with application to maize, sugar beet, and sunflower crops , 2021, bioRxiv.
[32] Leland McInnes,et al. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction , 2018, ArXiv.
[33] Hongyi Zhang,et al. mixup: Beyond Empirical Risk Minimization , 2017, ICLR.
[34] Frédéric Baret,et al. Ear density estimation from high resolution RGB imagery using deep learning technique , 2019, Agricultural and Forest Meteorology.