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Работы, на которые ссылается эта работа
Работ: 57
Работа: Prototype-based Incremental Few-Shot Semantic Segmentation
Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren +1
Статья2016Цитирований: 61ABIFully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, Trevor Darrell
Препринт2015Цитирований: 12ABIMicrosoft COCO: Common Objects in Context
Tsung-Yi Lin, Michael Maire, Serge Belongie +5
Глава2014Цитирований: 7ABIEncoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou +2
Глава2018Цитирований: 7ABIBatch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Препринт2024Цитирований: 5ABIPyramid Scene Parsing Network
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi +2
Статья2017Цитирований: 3ABIOvercoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz +11
Статья2017Цитирований: 3ABIRethinking Atrous Convolution for Semantic Image Segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff +1
Препринт2017Цитирований: 3ABIModel-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn, Pieter Abbeel, Sergey Levine
Препринт2017Цитирований: 2ABIDistilling the Knowledge in a Neural Network
Geoffrey E. Hinton, Oriol Vinyals, Jay B. Dean
Препринт2015Цитирований: 2ABIOn First-Order Meta-Learning Algorithms
Alex Nichol, Joshua Achiam, John Schulman
Препринт2018Цитирований: 2ABIThe Pascal Visual Object Classes Challenge: A Retrospective
Mark Everingham, S. M. Ali Eslami, Luc Van Gool +3
Статья2014Цитирований: 2ABI