Page 118 - 《武汉大学学报(信息科学版)》2025年第9期
P. 118
1846 武 汉 大 学 学 报 (信 息 科 学 版) 2025 年 9 月
al. Machine Learning Paradigms in High-Resolution Learning Sparse Switchable Normalization via
Remote Sensing Image Interpretation[J]. National SparsestMax[J]. International Journal of Computer
Remote Sensing Bulletin, 2021, 25(1): 182-197. Vision, 2020, 128(8): 2107-2125.
[8] 刘建伟, 赵会丹, 罗雄麟, 等 . 深度学习批归一化 [21] LI B , WU F , WEINBERGER K Q , et al. Posi⁃
及其相关算法研究进展[J]. 自动化学报, 2020, 46 tional Normalization[C]//Neural Information Pro⁃
(6): 1090-1120. cessing Systems, Vancouver, Canada, 2019.
LIU Jianwei, ZHAO Huidan, LUO Xionglin, et al. [22] YAO Z, CAO Y, ZHENG S, et al. Cross-Itera⁃
Research Progress on Batch Normalization of Deep tion Batch Normalization[C]//Computer Vision and
Learning and Its Related Algorithms[J]. Acta Auto⁃ Pattern Recognition (CVPR) , Beijing, China,
matica Sinica, 2020, 46(6): 1090-1120. 2021.
[9] KRIZHEVSKY A, SUTSKEVER I, HINTON G [23] SINGH S, KRISHNAN S. Filter Response Nor⁃
E. ImageNet Classification with Deep Convolutional malization Layer: Eliminating Batch Dependence in
Neural Networks[J]. Communications of the ACM, the Training of Deep Neural Networks[C]//Com⁃
2017, 60(6): 84-90. puter Vision and Pattern Recognition (CVPR),
[10] CARANDINI M, HEEGER D J. Normalization as Seattle , USA, 2020.
a Canonical Neural Computation[J]. Nature Re⁃ [24] IOFFE S. Batch Renormalization : Towards Re⁃
views Neuroscience, 2012, 13: 51-62. ducing Minibatch Dependence in Batch-Normalized
[11] HEEGER D J. Normalization of Cell Responses in Models [EB/OL]. [2022-12-21] https://arxiv.
Cat Striate Cortex[J]. Visual Neuroscience, 1992, org/abs/1702. 03275v2.
9(2): 181-197. [25] SONG Y B, XIANG J, JIANG J W, et al. A
[12] IOFFE S,SZEGEDY C. Batch Normalization: Ac⁃ Cross-Domain Change Detection Network Based on
celerating Deep Network Training by Reducing Inter⁃ Instance Normalization[J]. Remote Sensing, 2023,
nal Covariate Shift[J]. CoRR, 2015(1): 448–456. 15(24): 5785.
[13] PENG C, XIAO T T, LI Z M, et al. MegDet: A [26] QIAO S Y, WANG H Y, LIU C X, et al. Weight
Large Mini-Batch Object Detector[C]//Computer Standardization[EB/OL]. [2009-01-23] https://
Vision and Pattern Recognition, Salt Lake City, arxiv. org/abs/1903. 10520.
USA, 2018. [27] CHEN Peng, WANG Benkang, GAO Sa, et al.
[14] WU Y X,HE K M. Group Normalization[C]//Eu⁃ Building Collapse Assessment with Residual Net⁃
ropean Conference on Computer Vision (ECCV), work[J]. Geomatics and Information Science of Wu⁃
Munich, Germany, 2018. han University, 2020, 45(8): 1179-1184.
[15] HE K M, ZHANG X Y, REN S Q, et al. Delving [28] SZEGEDY C, LIU W, JIA Y Q, et al. Going
Deep into Rectifiers: Surpassing Human-Level Per⁃ Deeper with Convolutions[C]//Computer Vision
formance on ImageNet Classification[C]//IEEE In⁃ and Pattern Recognition (CVPR), Long Beach,
ternational Conference on Computer Vision (IC⁃ USA, 2019.
CV), Santiago, Chile, 2015. [29] KAZIMI B, SANDFELD S. Enhancing Semantic
[16] CHENG G, HAN J W, LU X Q. Remote Sensing Segmentation in High-Resolution TEM Images: A
Image Scene Classification: Benchmark and State of Comparative Study of Batch Normalization and
the Art[J]. IEEE, 2017, 105(10): 1865-1883. Instance Normalization [ J ]. Microscopy and
[17] SHARMA S, KULKARNI R, AJITHAPRASAD Microanalysis , 2024, 1: 1527-1546.
S, et al. Fringe Pattern Normalization Algorithm [30] HUANGI L, HUANGI L, YANG D W, et al.
Using Kalman Filter[J]. Results in Optics, 2021, 5 Decorrelated Batch Normalization[C]//IEEE/CVF
(1): 100152. Conference on Computer Vision and Pattern Recog⁃
[18] ULYANOV D, VEDALDI A, LEMPITSKY V. nition, Salt Lake City, USA, 2018.
Instance Normalization: The Missing Ingredient for [31] VRIES H D , STRUB F , JÉRÉMIE M , et al.
Fast Stylization[EB/OL]. [2016-05-17] https:// Modulating Early Visual Processing by Language
arxiv. org/abs/1607. 08022v3. [EB/OL]. [2017-11-12] https://arxiv. org/abs/
[19] BA J, KIROS J, HINTON G E. Layer Normaliza⁃ 1707. 00683.
tion[EB/OL]. [2016-06-14] https://arxiv. org/ [32] SINGH S, SHRIVASTAVA A. EvalNorm: Esti⁃
abs/1607. 06450. mating Batch Normalization Statistics for Evaluation
[20] SHAO W Q, LI J Y, REN J M, et al. SSN: [C]//IEEE/CVF International Conference on Com⁃

