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Vision-Language Pretraining (VLP) has demonstrated remarkable capabilities in learning visual representations from textual descriptions of images without annotations.
Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton · 2008
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Machine learning of hierarchical clustering to segment 2d and 3d images
Juan Nunez-Iglesias, Ryan Kennedy, Toufiq Parag, Jianbo Shi, and Dmitri B Chklovskii · 2013
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Crowdsourcing the creation of image segmentation algorithms for connectomics
Ignacio Arganda-Carreras, Srinivas C Turaga, Daniel R Berger, Dan Cireşan, Alessandro Giusti, Luca M Gambardella, Jürgen Schmidhuber, Dmitry Laptev, Sarvesh Dwivedi, Joachim M Buhmann, et al · 2015
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Unsupervised visual representation learning by context prediction
Carl Doersch, Abhinav Gupta, and Alexei A Efros · 2015
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Saturated reconstruction of a volume of neocortex
Narayanan Kasthuri, Kenneth Jeffrey Hayworth, Daniel Raimund Berger, Richard Lee Schalek, José Angel Conchello, Seymour Knowles-Barley, Dongil Lee, Amelio Vázquez-Reina, Verena Kaynig, Thouis Raymond Jones, et al · 2015
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Miccai challenge on circuit reconstruction from electron microscopy images, 2016
J Funke, S Saalfeld, DD Bock, SC Turaga, and E Perlman · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
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Colorful image colorization
Richard Zhang, Phillip Isola, and Alexei A Efros · 2016
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A connectome of a learning and memory center in the adult drosophila brain
Shin-ya Takemura, Yoshinori Aso, Toshihide Hige, Allan Wong, Zhiyuan Lu, C Shan Xu, Patricia K Rivlin, Harald Hess, Ting Zhao, Toufiq Parag, et al · 2017
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Large scale image segmentation with structured loss based deep learning for connectome reconstruction
Jan Funke, Fabian Tschopp, William Grisaitis, Arlo Sheridan, Chandan Singh, Stephan Saalfeld, and Srinivas C Turaga · 2018
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Unsupervised representation learning by predicting image rotations
Spyros Gidaris, Praveer Singh, and Nikos Komodakis · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Bootstrap your own latent-a new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, 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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Biobert: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang · 2020
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Self-supervised learning of pretext-invariant representations
Ishan Misra and Laurens van der Maaten · 2020
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Medicat: A dataset of medical images, captions, and textual references
Sanjay Subramanian, Lucy Lu Wang, Sachin Mehta, Ben Bogin, Madeleine van Zuylen, Sravanthi Parasa, Sameer Singh, Matt Gardner, and Hannaneh Hajishirzi · 2020
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Mitoem dataset: Large-scale 3d mitochondria instance segmentation from em images
Donglai Wei, Zudi Lin, Daniel Franco-Barranco, Nils Wendt, Xingyu Liu, Wenjie Yin, Xin Huang, Aarush Gupta, Won-Dong Jang, Xueying Wang, et al · 2020
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Making the most of text semantics to improve biomedical vision–language processing
Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel C Castro, Anton Schwaighofer, Stephanie Hyland, Maria Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, et al · 2022
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Data-driven surrogate model with latent data assimilation: Application to wildfire forecasting
Sibo Cheng, I Colin Prentice, Yuhan Huang, Yufang Jin, Yi-Ke Guo, and Rossella Arcucci · 2022
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Semi-supervised neuron segmentation via reinforced consistency learning
Wei Huang, Chang Chen, Zhiwei Xiong, Yueyi Zhang, Xuejin Chen, Xiaoyan Sun, and Feng Wu · 2022
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Self-supervised pre-training of swin transformers for 3d medical image analysis
Yucheng Tang, Dong Yang, Wenqi Li, Holger R Roth, Bennett Landman, Daguang Xu, Vishwesh Nath, and Ali Hatamizadeh · 2022
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Expert-level detection of pathologies from unannotated chest x-ray images via self-supervised learning
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Contrastive learning of medical visual representations from paired images and text
Yuhao Zhang, Hang Jiang, Yasuhide Miura, Christopher D Manning, and Curtis P Langlotz · 2020
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Exploring simple siamese representation learning
Xinlei Chen and Kaiming He · 2021
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Gloria: A multimodal global-local representation learning framework for label-efficient medical image recognition
Shih-Cheng Huang, Liyue Shen, Matthew P Lungren, and Serena Yeung · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Automatic detection of synaptic partners in a whole-brain drosophila em dataset
Philipp Schlegel, Alexander S Bates, Tejal Parag, Gregory SXE Jefferis, and Davi D Bock · 2021
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Barlow twins: Self-supervised learning via redundancy reduction
Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and Stéphane Deny · 2021
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Ekin Tiu, Ellie Talius, Pujan Patel, Curtis P Langlotz, Andrew Y Ng, and Pranav Rajpurkar · 2022
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Spatio-temporal contrastive learning enhanced gnns for session-based recommendation
Zhongwei Wan, Benyou Wang, Xin Liu, Jiezhong Qiu, Boyu Li, Ting Guo, Guangyong Chen, and Yang Wang · 2022
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Multi-granularity cross-modal alignment for generalized medical visual representation learning
Fuying Wang, Yuyin Zhou, Shujun Wang, Varut Vardhanabhuti, and Lequan Yu · 2022
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Stare at what you see: Masked image modeling without reconstruction
Hongwei Xue, Peng Gao, Hongyang Li, Yu Qiao, Hao Sun, Houqiang Li, and Jiebo Luo · 2022
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Universeg: Universal medical image segmentation
Victor Ion Butoi, Jose Javier Gonzalez Ortiz, Tianyu Ma, Mert R Sabuncu, John Guttag, and Adrian V Dalca · 2023
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Sibo Cheng, César Quilodrán-Casas, Said Ouala, Alban Farchi, Che Liu, Pierre Tandeo, Ronan Fablet, Didier Lucor, Bertrand Iooss, Julien Brajard, et al · 2023
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Frozen language model helps ecg zero-shot learning
Jun Li, Che Liu, Sibo Cheng, Rossella Arcucci, and Shenda Hong · 2023
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Clip-driven universal model for organ segmentation and tumor detection
Jie Liu, Yixiao Zhang, Jie-Neng Chen, Junfei Xiao, Yongyi Lu, Bennett A Landman, Yixuan Yuan, Alan Yuille, Yucheng Tang, and Zongwei Zhou · 2023
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Med-unic: Unifying cross-lingual medical vision-language pre-training by diminishing bias
Zhongwei Wan, Che Liu, Mi Zhang, Jie Fu, Benyou Wang, Sibo Cheng, Lei Ma, César Quilodrán-Casas, and Rossella Arcucci · 2023
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Uniseg: A prompt-driven universal segmentation model as well as a strong representation learner
Yiwen Ye, Yutong Xie, Jianpeng Zhang, Ziyang Chen, and Yong Xia · 2023
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