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Sequence modeling plays a vital role across various domains, with recurrent neural networks being historically the predominant method of performing these tasks.
A new approach to linear filtering and prediction problems
Rudolph Emil Kalman · 1960
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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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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Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
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A novel method for implementation of frameless stereoeeg in epilepsy surgery
Mark Nowell, Roman Rodionov, Beate Diehl, Tim Wehner, Gergely Zombori, Jane Kinghorn, Sebastien Ourselin, John Duncan, Anna Miserocchi, and Andrew McEvoy · 2014
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Mimic-iii, a freely accessible critical care database
Alistair E W Johnson, Tom J Pollard, Lu Shen, Li-wei H Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark · 2016
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Fully-convolutional siamese networks for object tracking
Luca Bertinetto, Jack Valmadre, Joao F. Henriques, Andrea Vedaldi, and Philip H. S. Torr · 2016
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the problem solved?
Olivier Bernard, Alain Lalande, Clement Zotti, Frederick Cervenansky, Xin Yang, Pheng-Ann Heng, Irem Cetin, Karim Lekadir, Oscar Camara, Miguel Angel Gonzalez Ballester, et al · 2018
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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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Hippo: Recurrent memory with optimal polynomial projections, 2020
Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, and Christopher Re · 2020
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Inferring super-resolution depth from a moving light-source enhanced rgb-d sensor: a variational approach
Lu Sang, Bjoern Haefner, and Daniel Cremers · 2020
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Cnn variants for computer vision: History, architecture, application, challenges and future scope
Dulari Bhatt, Chirag Patel, Hardik Talsania, Jigar Patel, Rasmika Vaghela, Sharnil Pandya, Kirit Modi, and Hemant Ghayvat · 2021
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Transunet: Transformers make strong encoders for medical image segmentation
Jieneng Chen, Yongyi Lu, Qihang Yu, Xiangde Luo, Ehsan Adeli, Yan Wang, Le Lu, Alan L Yuille, and Yuyin Zhou · 2021
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Brain tumor detection analysis using cnn: a review
Sunil Kumar, Renu Dhir, and Nisha Chaurasia · 2021
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Combining recurrent, convolutional, and continuous-time models with linear state-space layers, 2021
Albert Gu, Isys Johnson, Karan Goel, Khaled Saab, Tri Dao, Atri Rudra, and Christopher Ré · 2021
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Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 2021
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Medical image segmentation with limited supervision: a review of deep network models
Jialin Peng and Ye Wang · 2021
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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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Convolutional neural networks in medical image understanding: a survey
DR Sarvamangala and Raghavendra V Kulkarni · 2022
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Transformers in vision: A survey
Salman Khan, Muzammal Naseer, Munawar Hayat, Syed Waqas Zamir, Fahad Shahbaz Khan, and Mubarak Shah · 2022
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Building efficient cnn architectures for histopathology images analysis: A case-study in tumor-infiltrating lymphocytes classification
André LS Meirelles, Tahsin Kurc, Jun Kong, Renato Ferreira, Joel H Saltz, and George Teodoro · 2022
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Modeling long-range dependencies for weakly supervised disease classification and localization on chest x-ray
Fangyun Li, Lingxiao Zhou, Yunpeng Wang, Chuan Chen, Shuyi Yang, Fei Shan, and Lei Liu · 2022
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Efficient transformers: A survey
Yi Tay, Mostafa Dehghani, Dara Bahri, and Donald Metzler · 2022
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Billion-scale pretraining with vision transformers for multi-task visual representations
Josh Beal, Hao-Yu Wu, Dong Huk Park, Andrew Zhai, and Dmitry Kislyuk · 2022
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Efficiently modeling long sequences with structured state spaces, 2022
Albert Gu, Karan Goel, and Christopher Ré · 2022
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On the parameterization and initialization of diagonal state space models, 2022
Albert Gu, Ankit Gupta, Karan Goel, and Christopher Ré · 2022
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Diagonal state spaces are as effective as structured state spaces, 2022
Ankit Gupta, Albert Gu, and Jonathan Berant · 2022
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What makes convolutional models great on long sequence modeling?, 2022
Yuhong Li, Tianle Cai, Yi Zhang, Deming Chen, and Debadeepta Dey · 2022
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Long range language modeling via gated state spaces, 2022
Harsh Mehta, Ankit Gupta, Ashok Cutkosky, and Behnam Neyshabur · 2022
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Medical image segmentation on mri images with missing modalities: A review
Reza Azad, Nika Khosravi, Mohammad Dehghanmanshadi, Julien Cohen-Adad, and Dorit Merhof · 2022
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Deep learning for medical image analysis
S Kevin Zhou, Hayit Greenspan, and Dinggang Shen · 2023
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A comprehensive review of deep neural networks for medical image processing: Recent developments and future opportunities
Pawan Kumar Mall, Pradeep Kumar Singh, Swapnita Srivastav, Vipul Narayan, Marcin Paprzycki, Tatiana Jaworska, and Maria Ganzha · 2023
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Advances in medical image analysis with vision transformers: a comprehensive review
Reza Azad, Amirhossein Kazerouni, Moein Heidari, Ehsan Khodapanah Aghdam, Amirali Molaei, Yiwei Jia, Abin Jose, Rijo Roy, and Dorit Merhof · 2023
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A survey of visual transformers
Yang Liu, Yao Zhang, Yixin Wang, Feng Hou, Jin Yuan, Jiang Tian, Yang Zhang, Zhongchao Shi, Jianping Fan, and Zhiqiang He · 2023
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A survey on deep learning applied to medical images: from simple artificial neural networks to generative models
Pedro Celard, Eva Lorenzo Iglesias, José Manuel Sorribes-Fdez, Rubén Romero, A Seara Vieira, and Lourdes Borrajo · 2023
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Fusion of u-net and cnn model for segmentation and classification of skin lesion from dermoscopy images
Vatsala Anand, Sheifali Gupta, Deepika Koundal, and Karamjeet Singh · 2023
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Brain tumor segmentation and classification using hybrid deep cnn with lunetclassifier
T Balamurugan and E Gnanamanoharan · 2023
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Lightweight deep cnn-based models for early detection of covid-19 patients from chest x-ray images
Haval I Hussein, Abdulhakeem O Mohammed, Masoud M Hassan, and Ramadhan J Mstafa · 2023
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Gil-cnn: A novel multipath features for covid-19 detection using ct-scan images
N Jagan Mohan and DN Kiran Pandiri · 2023
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Multiple brain tumor classification with dense cnn architecture using brain mri images
Osman Özkaraca, Okan İhsan Bağrıaçık, Hüseyin Gürüler, Faheem Khan, Jamil Hussain, Jawad Khan, and Umm e Laila · 2023
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High accuracy hybrid cnn classifiers for breast cancer detection using mammogram and ultrasound datasets
Adyasha Sahu, Pradeep Kumar Das, and Sukadev Meher · 2023
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Transformers in medical imaging: A survey
Fahad Shamshad, Salman Khan, Syed Waqas Zamir, Muhammad Haris Khan, Munawar Hayat, Fahad Shahbaz Khan, and Huazhu Fu · 2023
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Transformers in medical image analysis
Kelei He, Chen Gan, Zhuoyuan Li, Islem Rekik, Zihao Yin, Wen Ji, Yang Gao, Qian Wang, Junfeng Zhang, and Dinggang Shen · 2023
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Hiformer: Hierarchical multi-scale representations using transformers for medical image segmentation
Moein Heidari, Amirhossein Kazerouni, Milad Soltany, Reza Azad, Ehsan Khodapanah Aghdam, Julien Cohen-Adad, and Dorit Merhof · 2023
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Mamba: Linear-time sequence modeling with selective state spaces, 2023
Albert Gu and Tri Dao · 2023
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Hungry hungry hippos: Towards language modeling with state space models, 2023
Daniel Y. Fu, Tri Dao, Khaled K. Saab, Armin W. Thomas, Atri Rudra, and Christopher Ré · 2023
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Simplified state space layers for sequence modeling, 2023
Jimmy T. H. Smith, Andrew Warrington, and Scott W. Linderman · 2023
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Simple hardware-efficient long convolutions for sequence modeling, 2023
Daniel Y. Fu, Elliot L. Epstein, Eric Nguyen, Armin W. Thomas, Michael Zhang, Tri Dao, Atri Rudra, and Christopher Ré · 2023
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Hyena hierarchy: Towards larger convolutional language models, 2023
Michael Poli, Stefano Massaroli, Eric Nguyen, Daniel Y. Fu, Tri Dao, Stephen Baccus, Yoshua Bengio, Stefano Ermon, and Christopher Ré · 2023
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Rwkv: Reinventing rnns for the transformer era, 2023
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Mega: Moving average equipped gated attention, 2023
Xuezhe Ma, Chunting Zhou, Xiang Kong, Junxian He, Liangke Gui, Graham Neubig, Jonathan May, and Luke Zettlemoyer · 2023
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Retentive network: A successor to transformer for large language models, 2023
Zigma: Zigzag mamba diffusion model
Vincent Tao Hu, Stefan Andreas Baumann, Ming Gui, Olga Grebenkova, Pingchuan Ma, Johannes Fischer, and Bjorn Ommer · 2024
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Mamba-nd: Selective state space modeling for multi-dimensional data
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Tao Huang, Xiaohuan Pei, Shan You, Fei Wang, Chen Qian, and Chang Xu · 2024
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Chenhongyi Yang, Zehui Chen, Miguel Espinosa, Linus Ericsson, Zhenyu Wang, Jiaming Liu, and Elliot J Crowley · 2024
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Vivim: a video vision mamba for medical video object segmentation, 2024
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Loss functions in the era of semantic segmentation: A survey and outlook
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Self-supervised learning for medical image classification: a systematic review and implementation guidelines
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Multimodal recurrence scoring system for prediction of clear cell renal cell carcinoma outcome: a discovery and validation study
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Prioritizing prognostic-associated subpopulations and individualized recurrence risk signatures from single-cell transcriptomes of colorectal cancer
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Unbiased curriculum learning enhanced global-local graph neural network for protein thermodynamic stability prediction
Haifan Gong, Yumeng Zhang, Chenhe Dong, Yue Wang, Guanqi Chen, Bilin Liang, Haofeng Li, Lanxuan Liu, Jie Xu, and Guanbin Li · 2023
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Foundational models in medical imaging: A comprehensive survey and future vision
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Yijun Yang, Zhaohu Xing, Chunwang Huang, and Lei Zhu · 2024
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Shu Yang, Yihui Wang, and Hao Chen · 2024
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Haifan Gong, Luoyao Kang, Yitao Wang, Xiang Wan, and Haofeng Li · 2024
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Ying Chen, Jiajing Xie, Yuxiang Lin, Yuhang Song, Wenxian Yang, and Rongshan Yu · 2024
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Zijie Fang, Yifeng Wang, Zhi Wang, Jian Zhang, Xiangyang Ji, and Yongbing Zhang · 2024
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Fd-vision mamba for endoscopic exposure correction, 2024
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Integrating mamba sequence model and hierarchical upsampling network for accurate semantic segmentation of multiple sclerosis legion, 2024
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