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We introduce a novel fine-grained dataset and benchmark, the Danish Fungi 2020 (DF20).
Automated flower classification over a large number of classes
Maria-Elena Nilsback and Andrew Zisserman · 2008
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https://svampe.databasen.org, 2009
Danish Mycological Society · 2009
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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The pascal visual object classes (voc) challenge
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2010
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Convolutional deep belief networks on cifar-10, 2010
Alex Krizhevsky · 2010
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The Caltech-UCSD Birds-200-2011 Dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
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Novel dataset for fine-grained image categorization : Stanford dogs
Aditya Khosla, Nityananda Jayadevaprakash, Bangpeng Yao, and Fei-Fei Li · 2012
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Leafsnap: A computer vision system for automatic plant species identification
Neeraj Kumar, Peter N. Belhumeur, Arijit Biswas, David W. Jacobs, W. John Kress, Ida Lopez, and João V. B. Soares · 2012
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Dog breed classification using part localization
Jiongxin Liu, Angjoo Kanazawa, David Jacobs, and Peter Belhumeur · 2012
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3d object representations for fine-grained categorization
Jonathan Krause, Michael Stark, Jia Deng, and Fei Fei Li · 2013
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Fine-grained visual classification of aircraft
S. Maji, J. Kannala, E. Rahtu, M. Blaschko, and A. Vedaldi · 2013
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Birdsnap: Large-scale fine-grained visual categorization of birds
Thomas Berg, Jiongxin Liu, Seung Woo Lee, Michelle L. Alexander, David W. Jacobs, and Peter N. Belhumeur · 2014
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Bird species categorization using pose normalized deep convolutional nets
Steve Branson, Grant Van Horn, Serge Belongie, and Pietro Perona · 2014
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Lifeclef 2015: multimedia life species identification challenges
Alexis Joly, Hervé Goëau, Hervé Glotin, Concetto Spampinato, Pierre Bonnet, Willem-Pier Vellinga, Robert Planqué, Andreas Rauber, Simone Palazzo, Bob Fisher, et al · 2015
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Bilinear cnn models for fine-grained visual recognition
Tsung-Yu Lin, Aruni RoyChowdhury, and Subhransu Maji · 2015
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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Building a bird recognition app and large scale dataset with citizen scientists: The fine print in fine-grained dataset collection
Grant Van Horn, Steve Branson, Ryan Farrell, Scott Haber, Jessie Barry, Panos Ipeirotis, Pietro Perona, and Serge Belongie · 2015
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Image classification with orchard metadata
Suchet Bargoti and James Underwood · 2016
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Plant identification in an open-world (lifeclef 2016)
Hervé Goëau, Pierre Bonnet, and Alexis Joly · 2016
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Taxonomy-regularized semantic deep convolutional neural networks
Wonjoon Goo, Juyong Kim, Gunhee Kim, and Sung Ju Hwang · 2016
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
The unreasonable effectiveness of noisy data for fine-grained recognition
Jonathan Krause, Benjamin Sapp, Andrew Howard, Howard Zhou, Alexander Toshev, Tom Duerig, James Philbin, and Li Fei-Fei · 2016
Cited alongside, same era.
Deep metric learning via lifted structured feature embedding
Hyun Oh Song, Yu Xiang, Stefanie Jegelka, and Silvio Savarese · 2016
Cited alongside, same era.
Improved deep metric learning with multi-class n-pair loss objective
Kihyuk Sohn · 2016
Cited alongside, same era.
Picking deep filter responses for fine-grained image recognition
Xiaopeng Zhang, Hongkai Xiong, Wengang Zhou, Weiyao Lin, and Qi Tian · 2016
The inaturalist species classification and detection dataset
Grant Van Horn, Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Alex Shepard, Hartwig Adam, Pietro Perona, and Serge Belongie · 2018
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Attngan: Fine-grained text to image generation with attentional generative adversarial networks
Tao Xu, Pengchuan Zhang, Qiuyuan Huang, Han Zhang, Zhe Gan, Xiaolei Huang, and Xiaodong He · 2018
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Interpretable convolutional neural networks
Quanshi Zhang, Ying Nian Wu, and Song-Chun Zhu · 2018
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Improving plankton image classification using context metadata
Jeffrey S Ellen, Casey A Graff, and Mark D Ohman · 2019
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Danish mycological society, fungal records database, 2019
Tobias Guldberg Frøslev, Jacob Heilmann-Clausen, Christian Lange, Thomas Læssøe, Jens Henrik Petersen, Ulrik Søchting, Thomas Stjernegaard Jeppesen, and Jan Vesterholt · 2019
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Cited alongside, same era.
Fine-grained recognition in the wild: A multi-task domain adaptation approach
Timnit Gebru, Judy Hoffman, and Li Fei-Fei · 2017
Cited alongside, same era.
Plant identification based on noisy web data: the amazing performance of deep learning (lifeclef 2017)
Herve Goeau, Pierre Bonnet, and Alexis Joly · 2017
Cited alongside, same era.
On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger · 2017
Cited alongside, same era.
Vegfru: A domain-specific dataset for fine-grained visual categorization
Saihui Hou, Yushan Feng, and Zilei Wang · 2017
Cited alongside, same era.
Learning without forgetting
Zhizhong Li and Derek Hoiem · 2017
Cited alongside, same era.
Inception-v4, inception-resnet and the impact of residual connections on learning
Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, and Alexander A Alemi · 2017
Cited alongside, same era.
How citizen science boosted primary knowledge on fungal biodiversity in denmark
Jacob Heilmann-Clausen, Hans Henrik Bruun, Rasmus Ejrnæs, Tobias Guldberg Frøslev, Thomas Læssøe, and Jens H. Petersen · 2019
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Presence-only geographical priors for fine-grained image classification
Oisin Mac Aodha, Elijah Cole, and Pietro Perona · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Improving cnn classifiers by estimating test-time priors
Milan Sulc and Jiri Matas · 2019
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Efficientnet: Rethinking model scaling for convolutional neural networks
Mingxing Tan and Quoc V Le · 2019
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Evaluating model calibration in classification
Juozas Vaicenavicius, David Widmann, Carl Andersson, Fredrik Lindsten, Jacob Roll, and Thomas Schön · 2019
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Few-shot learning with localization in realistic settings
Davis Wertheimer and Bharath Hariharan · 2019
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Classification is a strong baseline for deep metric learning
Andrew Zhai and Hao-Yu Wu · 2019
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Lucas Beyer, Olivier J Hénaff, Alexander Kolesnikov, Xiaohua Zhai, and Aäron van den Oord · 2020
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Albumentations: Fast and flexible image augmentations
Alexander Buslaev, Vladimir I. Iglovikov, Eugene Khvedchenya, Alex Parinov, Mikhail Druzhinin, and Alexandr A. Kalinin · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Fungi recognition: A practical use case
Milan Sulc, Lukas Picek, Jiri Matas, Thomas Jeppesen, and Jacob Heilmann-Clausen · 2020
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