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    year         = 2013,
    address      = {Nairobi, {Kenya}},
    institution  = {Kenya Wildlife Service},
    type         = {Tech. Rep.}
}
@techreport{patrick_demographic_2003,
    title        = {Demographic Status of the {Meru} Elephant Population},
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    year         = 2003,
    address      = {Nairobi, {Kenya}},
    institution  = {Kenya Wildlife Service},
    type         = {Tech. Rep.}
}
@techreport{rubenstein_great_2015,
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    type         = {Tech. Rep.}
}
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    title        = {The State of {Kenya’s} {Grevy’s} Zebras and Reticulated Giraffes: Results of the {Great} {Grevy’s} {Rally} 2018},
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    year         = 2018,
    address      = {Nairobi, {Kenya}},
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    type         = {Tech. Rep.}
}
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}
@unpublished{bastien_theano:_2012,
    title        = {{Theano}: New Features and Speed Improvements},
    author       = {Bastien, Fr{\'e}d{\'e}ric and Lamblin, Pascal and Pascanu, Razvan and Bergstra, James and Goodfellow, Ian J. and Bergeron, Arnaud and Bouchard, Nicolas and others},
    year         = 2012,
    note         = {arXiv:1211.5590}
}
@unpublished{beery_efficient_2019,
    title        = {Efficient Pipeline for Camera Trap Image Review},
    author       = {Beery, Sara and Morris, Dan and Yang, Siyu},
    year         = 2019,
    note         = {arXiv:1907.06772}
}
@unpublished{beery_iwildcam_2019,
    title        = {The {iWildCam} 2018 Challenge Dataset},
    author       = {Beery, Sara and Van Horn, Grant and Mac Aodha, Oisin and Perona, Pietro},
    year         = 2019,
    note         = {arXiv:1904.05986}
}
@unpublished{beery_recognition_2018,
    title        = {Recognition in Terra Incognita},
    author       = {Beery, Sara and Van Horn, Grant and Perona, Pietro},
    year         = 2018,
    note         = {arXiv:1807.04975}
}
@unpublished{bengio_advances_2012,
    title        = {Advances in Optimizing Recurrent Networks},
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    note         = {arXiv:1212.0901}
}
@unpublished{berger-wolf_wildbook_2017,
    title        = {Wildbook: Crowdsourcing, Computer Vision, and Data Science for Conservation},
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    year         = 2017,
    note         = {arXiv:1710.08880}
}
@unpublished{branson_bird_2014,
    title        = {Bird Species Categorization Using Pose Normalized Deep Convolutional Nets},
    author       = {Branson, Steve and Van Horn, Grant and Belongie, Serge and Perona, Pietro},
    year         = 2014,
    note         = {arXiv:1406.2952}
}
@unpublished{brunger_panoptic_2020,
    title        = {Panoptic Instance Segmentation on Pigs},
    author       = {Br{\"u}nger, Johannes and Gentz, Maria and Traulsen, Imke and Koch, Reinhard},
    year         = 2020,
    note         = {arXiv:2005.10499}
}
@unpublished{cai_cascade_2017,
    title        = {Cascade {R-CNN}: Delving Into High Quality Object Detection},
    author       = {Cai, Zhaowei and Vasconcelos, Nuno},
    year         = 2017,
    note         = {arXiv:1712.00726}
}
@unpublished{chen_semantic_2014,
    title        = {Semantic Image Segmentation With Deep Convolutional Nets and Fully Connected {CRFs}},
    author       = {Chen, Liang-Chieh and Papandreou, George and Kokkinos, Iasonas and Murphy, Kevin and Yuille, Alan L.},
    year         = 2014,
    note         = {arXiv:1412.7062}
}
@unpublished{cheng_revisiting_2018,
    title        = {Revisiting {R-CNN}: On Awakening the Classification Power of Faster {R-CNN}},
    author       = {Cheng, Bowen and Wei, Yunchao and Shi, Honghui and Feris, Rogerio and Xiong, Jinjun and Huang, Thomas},
    year         = 2018,
    note         = {arXiv:1803.06799}
}
@unpublished{chollet_xception_2017,
    title        = {{Xception}: Deep Learning With Depthwise Separable Convolutions},
    author       = {Chollet, François},
    year         = 2017,
    note         = {arXiv:1610.02357}
}
@unpublished{duan_centernet_2019,
    title        = {{CenterNet}: Keypoint Triplets for Object Detection},
    author       = {Duan, Kaiwen and Bai, Song and Xie, Lingxi and Qi, Honggang and Huang, Qingming and Tian, Qi},
    year         = 2019,
    note         = {arXiv:1904.08189}
}
@unpublished{fu_stacked_2019,
    title        = {Stacked Deconvolutional Network for Semantic Segmentation},
    author       = {Fu, Jun and Liu, Jing and Wang, Yuhang and Zhou, Jin and Wang, Changyong and Lu, Hanqing},
    year         = 2019,
    note         = {arXiv:1708.04943}
}
@unpublished{girshick_rich_2014,
    title        = {Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation},
    author       = {Girshick, Ross and Donahue, Jeff and Darrell, Trevor and Malik, Jitendra},
    year         = 2014,
    note         = {arXiv:1311.2524}
}
@unpublished{graham_spatially-sparse_2014,
    title        = {Spatially-sparse Convolutional Neural Networks},
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    year         = 2014,
    note         = {arXiv:1409.6070}
}
@unpublished{gu_understanding_2019,
    title        = {Understanding Bias in Machine Learning},
    author       = {Gu, Jindong and Oelke, Daniela},
    year         = 2019,
    note         = {arXiv:1909.01866}
}
@unpublished{hara_attentional_2017,
    title        = {Attentional Network for Visual Object Detection},
    author       = {Hara, Kota and Liu, Ming-Yu and Tuzel, Oncel and Farahmand, Amir-Massoud},
    year         = 2017,
    note         = {arXiv:1702.01478}
}
@unpublished{he_deep_2015,
    title        = {Deep Residual Learning for Image Recognition},
    author       = {He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
    year         = 2015,
    note         = {arXiv:1512.03385}
}
@unpublished{he_mask_2017,
    title        = {Mask {R-CNN}},
    author       = {He, Kaiming and Gkioxari, Georgia and Dollár, Piotr and Girshick, Ross},
    year         = 2017,
    note         = {arXiv:1703.06870}
}
@unpublished{hermans_defense_2017,
    title        = {In Defense of the Triplet Loss for Person Re-identification},
    author       = {Hermans, Alexander and Beyer, Lucas and Leibe, Bastian},
    year         = 2017,
    note         = {arXiv:1703.07737}
}
@unpublished{hinton_improving_2012,
    title        = {Improving Neural Networks by Preventing Co-adaptation of Feature Detectors},
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    year         = 2012,
    note         = {arXiv:1207.0580}
}
@unpublished{hosang_learning_2017,
    title        = {Learning Non-maximum Suppression},
    author       = {Hosang, Jan and Benenson, Rodrigo and Schiele, Bernt},
    year         = 2017,
    note         = {arXiv:1705.02950}
}
@unpublished{hosang_what_2015,
    title        = {What Makes for Effective Detection Proposals?},
    author       = {Hosang, Jan and Benenson, Rodrigo and Dollár, Piotr and Schiele, Bernt},
    year         = 2015,
    note         = {arXiv:1502.05082}
}
@unpublished{howard_mobilenets_2017,
    title        = {{MobileNets}: Efficient Convolutional Neural Networks for Mobile Vision Applications},
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    year         = 2017,
    note         = {arXiv:1704.04861}
}
@unpublished{huang_densely_2016,
    title        = {Densely Connected Convolutional Networks},
    author       = {Huang, Gao and Liu, Zhuang and Van Der Maaten, Laurens and Weinberger, Kilian Q.},
    year         = 2016,
    note         = {arXiv:1608.06993}
}
@unpublished{iandola_densenet:_2014,
    title        = {{Densenet}: Implementing Efficient Convnet Descriptor Pyramids},
    author       = {Iandola, Forrest and Moskewicz, Matt and Karayev, Sergey and Girshick, Ross and Darrell, Trevor and Keutzer, Kurt},
    year         = 2014,
    note         = {arXiv:1404.1869}
}
@unpublished{iandola_squeezenet:_2016,
    title        = {{SqueezeNet}: {AlexNet}-level Accuracy With 50x Fewer Parameters and {\textless}0.5MB Model Size},
    author       = {Iandola, Forrest N. and Han, Song and Moskewicz, Matthew W. and Ashraf, Khalid and Dally, William J. and Keutzer, Kurt},
    year         = 2016,
    note         = {arXiv:1602.07360}
}
@unpublished{ioffe_batch_2015,
    title        = {Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift},
    author       = {Ioffe, Sergey and Szegedy, Christian},
    year         = 2015,
    note         = {arXiv:1502.03167}
}
@unpublished{ioffe_batch_2017,
    title        = {Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-normalized Models},
    author       = {Ioffe, Sergey},
    year         = 2017,
    note         = {arXiv:1702.03275}
}
@unpublished{jin_how_2017,
    title        = {How to Escape Saddle Points Efficiently},
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    year         = 2017,
    note         = {arXiv:1703.00887}
}
@unpublished{keskar_improving_2017,
    title        = {Improving Generalization Performance by Switching From {Adam} to {SGD}},
    author       = {Keskar, Nitish Shirish and Socher, Richard},
    year         = 2017,
    note         = {arXiv:1712.07628}
}
@unpublished{khan_animalweb_2019,
    title        = {{AnimalWeb}: A Large-scale Hierarchical Dataset of Annotated Animal Faces},
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    year         = 2019,
    note         = {arXiv:1909.04951}
}
@unpublished{kingma_adam:_2014,
    title        = {{Adam}: A Method for Stochastic Optimization},
    author       = {Kingma, Diederik and Ba, Jimmy},
    year         = 2014,
    note         = {arXiv:1412.6980}
}
@unpublished{kosiorek_hierarchical_2017,
    title        = {Hierarchical Attentive Recurrent Tracking},
    author       = {Kosiorek, Adam R. and Bewley, Alex and Posner, Ingmar},
    year         = 2017,
    note         = {arXiv:1706.09262}
}
@unpublished{krizhevsky_one_2014,
    title        = {One Weird Trick for Parallelizing Convolutional Neural Networks},
    author       = {Krizhevsky, Alex},
    year         = 2014,
    note         = {arXiv:1404.5997}
}
@unpublished{kulits_elephantbook_2021,
    title        = {{ElephantBook}: A Semi-automated Human-in-the-loop System for Elephant Re-identification},
    author       = {Kulits, Peter and Wall, Jake and Bedetti, Anka and Henley, Michelle and Beery, Sara},
    year         = 2021,
    note         = {arXiv:2106.15083}
}
@unpublished{kummerer_deep_2014,
    title        = {{DeepGaze} {I}: Boosting Saliency Prediction With Feature Maps Trained on {ImageNet}},
    author       = {K{\"u}mmerer, Matthias and Theis, Lucas and Bethge, Matthias},
    year         = 2014,
    note         = {arXiv:1411.1045}
}
@unpublished{kummerer_deepgaze_2016,
    title        = {{DeepGaze} {II}: Reading Fixations From Deep Features Trained on Object Recognition},
    author       = {K{\"u}mmerer, Matthias and Wallis, Thomas {SA} and Bethge, Matthias},
    year         = 2016,
    note         = {arXiv:1610.01563}
}
@unpublished{lee_deeply-supervised_2014,
    title        = {Deeply-supervised Nets},
    author       = {Lee, Chen-Yu and Xie, Saining and Gallagher, Patrick and Zhang, Zhengyou and Tu, Zhuowen},
    year         = 2014,
    note         = {arXiv:1409.5185}
}
@unpublished{li_atrw_2019,
    title        = {{ATRW}: A Benchmark for {Amur} Tiger Re-identification in the Wild},
    author       = {Li, Shuyuan and Li, Jianguo and Tang, Hanlin and Qian, Rui and Lin, Weiyao},
    year         = 2019,
    note         = {arXiv:1906.05586}
}
@unpublished{li_lcnn:_2015,
    title        = {{LCNN}: Low-level Feature Embedded {CNN} for Salient Object Detection},
    author       = {Li, Hongyang and Lu, Huchuan and Lin, Zhe and Shen, Xiaohui and Price, Brian},
    year         = 2015,
    note         = {arXiv:1508.03928}
}
@unpublished{li_scale-aware_2019,
    title        = {Scale-aware Trident Networks for Object Detection},
    author       = {Li, Yanghao and Chen, Yuntao and Wang, Naiyan and Zhang, Zhaoxiang},
    year         = 2019,
    note         = {arXiv:1901.01892}
}
@unpublished{li_tiny-dsod_2018,
    title        = {{Tiny-DSOD}: Lightweight Object Detection for Resource-restricted Usages},
    author       = {Li, Yuxi and Li, Jiuwei and Lin, Weiyao and Li, Jianguo},
    year         = 2018,
    note         = {arXiv:1807.11013}
}
@unpublished{lin_feature_2017,
    title        = {Feature Pyramid Networks for Object Detection},
    author       = {Lin, Tsung-Yi and Dollár, Piotr and Girshick, Ross and He, Kaiming and Hariharan, Bharath and Belongie, Serge},
    year         = 2017,
    note         = {arXiv:1612.03144}
}
@unpublished{lin_focal_2018,
    title        = {Focal Loss for Dense Object Detection},
    author       = {Lin, Tsung-Yi and Goyal, Priya and Girshick, Ross and He, Kaiming and Dollár, Piotr},
    year         = 2017,
    note         = {arXiv:1708.02002}
}
@unpublished{lin_microsoft_2014,
    title        = {{Microsoft} {COCO}: Common Objects in Context},
    author       = {Lin, Tsung-Yi and Maire, Michael and Belongie, Serge and Bourdev, Lubomir and Girshick, Ross and Hays, James and Perona, Pietro and others},
    year         = 2014,
    note         = {arXiv:1405.0312}
}
@unpublished{lin_network_2013,
    title        = {Network In Network},
    author       = {Lin, Min and Chen, Qiang and Yan, Shuicheng},
    year         = 2013,
    note         = {arXiv:1312.4400}
}
@unpublished{liu_deep_2019,
    title        = {Deep Learning for Generic Object Detection: A Survey},
    author       = {Liu, Li and Ouyang, Wanli and Wang, Xiaogang and Fieguth, Paul and Chen, Jie and Liu, Xinwang and Pietikäinen, Matti},
    year         = 2019,
    note         = {arXiv:1809.02165}
}
@unpublished{ma_shufflenet_2018,
    title        = {{ShuffleNet} {V2}: Practical Guidelines for Efficient CNN Architecture Design},
    author       = {Ma, Ningning and Zhang, Xiangyu and Zheng, Hai-Tao and Sun, Jian},
    year         = 2018,
    note         = {arXiv:1807.11164}
}
@unpublished{melekhov_image-based_2017,
    title        = {Image-based Localization Using Hourglass Networks},
    author       = {Melekhov, Iaroslav and Ylioinas, Juha and Kannala, Juho and Rahtu, Esa},
    year         = 2017,
    note         = {arXiv:1703.07971}
}
@unpublished{mishkin_all_2015,
    title        = {All You Need Is a Good Init},
    author       = {Mishkin, Dmytro and Matas, Jiri},
    year         = 2015,
    note         = {arXiv:1511.06422}
}
@unpublished{moskvyak_robust_2019,
    title        = {Robust Re-identification of Manta Rays From Natural Markings by Learning Pose Invariant Embeddings},
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    year         = 2019,
    note         = {arXiv:1902.10847}
}
@unpublished{ouyang_deepid-net:_2014,
    title        = {{DeepID-Net}: Multi-stage and Deformable Deep Convolutional Neural Networks for Object Detection},
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    year         = 2014,
    note         = {arXiv:1409.3505}
}
@unpublished{pascanu_difficulty_2013,
    title        = {On the Difficulty of Training Recurrent Neural Networks},
    author       = {Pascanu, Razvan and Mikolov, Tomas and Bengio, Yoshua},
    year         = 2013,
    note         = {arXiv:1211.5063}
}
@unpublished{pascanu_understanding_2012,
    title        = {Understanding the Exploding Gradient Problem},
    author       = {Pascanu, Razvan and Mikolov, Tomas and Bengio, Yoshua},
    year         = 2012,
    note         = {arXiv:1211.5063}
}
@unpublished{pinheiro_learning_2015,
    title        = {Learning to Segment Object Candidates},
    author       = {Pinheiro, Pedro O. and Collobert, Ronan and Dollar, Piotr},
    year         = 2015,
    note         = {arXiv:1506.06204}
}
@unpublished{polzounov_right_2016,
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    author       = {Polzounov, Andrei and Terpugova, Ilmira and Skiparis, Deividas and Mihai, Andrei},
    year         = 2016,
    note         = {arXiv:1604.05605}
}
@unpublished{qiu_unrealcv:_2016,
    title        = {{UnrealCV}: Connecting Computer Vision to Unreal Engine},
    author       = {Qiu, Weichao and Yuille, Alan},
    year         = 2016,
    note         = {arXiv:1609.01326}
}
@unpublished{redmon_yolo9000:_2016,
    title        = {{YOLO9000}: Better, Faster, Stronger},
    author       = {Redmon, Joseph and Farhadi, Ali},
    year         = 2016,
    note         = {arXiv:1612.08242}
}
@unpublished{redmon_yolov3_2018,
    title        = {{YOLOv3}: An Incremental Improvement},
    author       = {Redmon, Joseph and Farhadi, Ali},
    year         = 2018,
    note         = {arXiv:1804.02767}
}
@unpublished{ronneberger_u-net:_2015,
    title        = {{U-Net}: Convolutional Networks for Biomedical Image Segmentation},
    author       = {Ronneberger, Olaf and Fischer, Philipp and Brox, Thomas},
    year         = 2015,
    note         = {arXiv:1505.04597}
}
@unpublished{ruder_overview_2016,
    title        = {An Overview of Gradient Descent Optimization Algorithms},
    author       = {Ruder, Sebastian},
    year         = 2016,
    note         = {arXiv:1609.04747}
}
@unpublished{schaul_no_2012,
    title        = {No More Pesky Learning Rates},
    author       = {Schaul, Tom and Zhang, Sixin and {LeCun}, Yann},
    year         = 2012,
    note         = {arXiv:1206.1106}
}
@unpublished{sermanet_overfeat:_2013,
    title        = {{Overfeat}: Integrated Recognition, Localization and Detection Using Convolutional Networks},
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    year         = 2013,
    note         = {arXiv:1312.6229}
}
@unpublished{simonyan_very_2014,
    title        = {Very Deep Convolutional Networks for Large-scale Image Recognition},
    author       = {Simonyan, Karen and Zisserman, Andrew},
    year         = 2014,
    note         = {arXiv:1409.1556}
}
@unpublished{springenberg_striving_2014,
    title        = {Striving for simplicity: The all convolutional net},
    author       = {Springenberg, Jost Tobias and Dosovitskiy, Alexey and Brox, Thomas and Riedmiller, Martin},
    year         = 2014,
    note         = {arXiv:1412.6806}
}
@unpublished{tan_mnasnet_2019,
    title        = {{MnasNet}: Platform-aware Neural Architecture Search for Mobile},
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    year         = 2019,
    note         = {arXiv:1807.11626}
}
@unpublished{taylor_improving_2017,
    title        = {Improving Deep Learning Using Generic Data Augmentation},
    author       = {Taylor, Luke and Nitschke, Geoff},
    year         = 2017,
    note         = {arXiv:1708.06020}
}
@unpublished{thompson_finfindr_2019,
    title        = {{finFindR}: Computer-assisted Recognition and Identification of Bottlenose Dolphin Photos in {R}},
    author       = {Thompson, Jaime W. and Zero, Victoria H. and Schwacke, Lori H. and Speakman, Todd R. and Quigley, Brian M. and Morey, Jeanine {SM} and {McDonald}, Trent L.},
    year         = 2019,
    note         = {bioRxiv:825661}
}
@unpublished{wan_bootstrapping_2016,
    title        = {Bootstrapping Face Detection With Hard Negative Examples},
    author       = {Wan, Shaohua and Chen, Zhijun and Zhang, Tao and Zhang, Bo and Wong, Kong-Kat},
    year         = 2016,
    note         = {arXiv:1608.02236}
}
@unpublished{wan_end--end_2014,
    title        = {End-to-end Integration of a Convolutional Network, Deformable Parts Model and Non-maximum Suppression},
    author       = {Wan, Li and Eigen, David and Fergus, Rob},
    year         = 2014,
    note         = {arXiv:1411.5309}
}
@unpublished{wang_attention-based_2017,
    title        = {An Attention-based Deep Net for Learning to Rank},
    author       = {Wang, Baiyang and Klabjan, Diego},
    year         = 2017,
    note         = {arXiv:1702.06106}
}
@unpublished{wang_survey_2016,
    title        = {Survey on the Attention Based {RNN} Model and Its Applications in Computer Vision},
    author       = {Wang, Feng and Tax, David M. J.},
    year         = 2016,
    note         = {arXiv:1601.06823}
}
@unpublished{xu_few-shot_2016,
    title        = {Few-shot Object Recognition From Machine-labeled Web Images},
    author       = {Xu, Zhongwen and Zhu, Linchao and Yang, Yi},
    year         = 2016,
    note         = {arXiv:1612.06152}
}
@unpublished{zagoruyko_wide_2016,
    title        = {Wide Residual Networks},
    author       = {Zagoruyko, Sergey and Komodakis, Nikos},
    year         = 2016,
    note         = {arXiv:1605.07146}
}
@unpublished{zhang_alignedreid_2017,
    title        = {{AlignedReID}: Surpassing Human-level Performance in Person Re-identification},
    author       = {Zhang, Xuan and Luo, Hao and Fan, Xing and Xiang, Weilai and Sun, Yixiao and Xiao, Qiqi and Jiang, Wei and others},
    year         = 2017,
    note         = {arXiv:1711.08184}
}
@unpublished{zhao_object_2019,
    title        = {Object Detection With Deep Learning: A Review},
    author       = {Zhao, Zhong-Qiu and Zheng, Peng and Xu, Shou-Tao and Wu, Xindong},
    year         = 2019,
    note         = {arXiv:1807.05511}
}