Jiamin Ren
Jiamin Ren
SenseTime Research
在 sensetime.com 的电子邮件经过验证
Differentiable learning-to-normalize via switchable normalization
P Luo*, J Ren*, Z Peng, R Zhang, J Li, (*equal contribution)
International Conference on Learning Representations, 2018
SSN: Learning Sparse Switchable Normalization via SparsestMax
W Shao, J Li, J Ren, R Zhang, X Wang, P Luo
International Journal of Computer Vision \ https://link.springer.com …, 2019
Object detection on panoramic images based on deep learning
D Fucheng, Z Xiaorui, R Jiamin
2017 3rd International Conference on Control, Automation and Robotics (ICCAR …, 2017
Switchable normalization for learning-to-normalize deep representation
P Luo, R Zhang, J Ren, Z Peng, J Li
IEEE transactions on pattern analysis and machine intelligence, 2019
Differentiable Dynamic Normalization for Learning Deep Representation
L Ping, P Zhanglin, S Wenqi, Z Ruimao, R Jiamin, W Lingyun
International Conference on Machine Learning, 4203-4211, 2019
Do normalization layers in a deep convnet really need to be distinct?
P Luo, Z Peng, J Ren, R Zhang
arXiv preprint arXiv:1811.07727, 2018
CUImage: A Neverending Learning Platform on a Convolutional Knowledge Graph of Billion Web Images
Z Peng, L Wu, J Ren, R Zhang, P Luo
2018 IEEE International Conference on Big Data (Big Data), 1787-1796, 2018
Video Classification via Relational Feature Encoding Networks
Y Zhou, J Ren, J Li, L Feng, S Qiu, P Luo
Proceedings of the Workshop on Large-Scale Video Classification Challenge, 9-13, 2017
UXNet: Searching Multi-level Feature Aggregation for 3D Medical Image Segmentation
Y Ji, R Zhang, Z Li, J Ren, S Zhang, P Luo
International Conference on Medical Image Computing and Computer-Assisted …, 2020
Normalization method and apparatus for deep neural network, and storage media
P Luo, L Wu, J Ren, P Zhanglin, R Zhang, W Xinjiang
US Patent App. 16/862,304, 2020
Scheduling Large-scale Distributed Training via Reinforcement Learning
Z Peng, J Ren, R Zhang, L Wu, X Wang, P Luo
2018 IEEE International Conference on Big Data (Big Data), 1797-1806, 2018
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