View-Semantic Transformer With Enhancing Diversity for Sparse-View SAR Target Recognition
暂无分享,去创建一个
[1] Yilong Yin,et al. Adaptive Feature Aggregation in Deep Multi-Task Convolutional Neural Networks , 2022, IEEE Transactions on Circuits and Systems for Video Technology.
[2] Quan Pan,et al. Rotation Awareness Based Self-Supervised Learning for SAR Target Recognition With Limited Training Samples , 2021, IEEE Transactions on Image Processing.
[3] Feng Xu,et al. Learning to Generate SAR Images With Adversarial Autoencoder , 2021, IEEE Transactions on Geoscience and Remote Sensing.
[4] Yudong Chen,et al. A Survey on Curriculum Learning , 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[5] Hongming Shan,et al. When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Xiaorui Ma,et al. Transfer Learning for SAR Image Classification Via Deep Joint Distribution Adaptation Networks , 2020, IEEE Transactions on Geoscience and Remote Sensing.
[7] Ekaterina Iakovleva,et al. Meta-Learning with Shared Amortized Variational Inference , 2020, ICML.
[8] Ching Y. Suen,et al. Towards Robust Pattern Recognition: A Review , 2020, Proceedings of the IEEE.
[9] Zongjie Cao,et al. LDGAN: A Synthetic Aperture Radar Image Generation Method for Automatic Target Recognition , 2020, IEEE Transactions on Geoscience and Remote Sensing.
[10] Aaron Hertzmann,et al. GANSpace: Discovering Interpretable GAN Controls , 2020, NeurIPS.
[11] Xianzhi Li,et al. PointAugment: An Auto-Augmentation Framework for Point Cloud Classification , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Michael I. Jordan,et al. AUTO-ENCODING VARIATIONAL BAYES , 2020 .
[13] Artem Babenko,et al. Unsupervised Discovery of Interpretable Directions in the GAN Latent Space , 2020, ICML.
[14] Bolei Zhou,et al. Interpreting the Latent Space of GANs for Semantic Face Editing , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[15] Phillip Isola,et al. On the "steerability" of generative adversarial networks , 2019, ICLR.
[16] Eric Eaton,et al. Deep Transfer Learning for Few-Shot SAR Image Classification , 2019, Remote. Sens..
[17] Peter Wonka,et al. Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space? , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[18] Zongjie Cao,et al. Image Data Augmentation for SAR Sensor via Generative Adversarial Nets , 2019, IEEE Access.
[19] Siwei Ma,et al. Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Feng Xu,et al. Reciprocal translation between SAR and optical remote sensing images with cascaded-residual adversarial networks , 2019, Science China Information Sciences.
[21] Yoshua Bengio,et al. MetaGAN: An Adversarial Approach to Few-Shot Learning , 2018, NeurIPS.
[22] Vladlen Koltun,et al. Multi-Task Learning as Multi-Objective Optimization , 2018, NeurIPS.
[23] Shih-Fu Chang,et al. Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks , 2018, NeurIPS.
[24] Lei Liu,et al. SAR Target Classification with CycleGAN Transferred Simulated Samples , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.
[25] Jianyu Yang,et al. SAR Automatic Target Recognition Based on Multiview Deep Learning Framework , 2018, IEEE Transactions on Geoscience and Remote Sensing.
[26] Wang Ping,et al. Research on data augmentation for image classification based on convolution neural networks , 2017, 2017 Chinese Automation Congress (CAC).
[27] Andrew Zisserman,et al. Multi-task Self-Supervised Visual Learning , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[28] Allan Aasbjerg Nielsen,et al. Improving SAR Automatic Target Recognition Models With Transfer Learning From Simulated Data , 2017, IEEE Geoscience and Remote Sensing Letters.
[29] Zhi Chen,et al. Adversarial Feature Matching for Text Generation , 2017, ICML.
[30] Yueting Zhang,et al. Synthetic Aperture Radar Image Synthesis by Using Generative Adversarial Nets , 2017, IEEE Geoscience and Remote Sensing Letters.
[31] Richard S. Zemel,et al. Prototypical Networks for Few-shot Learning , 2017, NIPS.
[32] Hong Yu,et al. Meta Networks , 2017, ICML.
[33] Arumugam Nallanathan,et al. Moving Target Recognition Based on Transfer Learning and Three-Dimensional Over-Complete Dictionary , 2016, IEEE Sensors Journal.
[34] Oriol Vinyals,et al. Matching Networks for One Shot Learning , 2016, NIPS.
[35] Andrea Vedaldi,et al. Integrated perception with recurrent multi-task neural networks , 2016, NIPS.
[36] Haipeng Wang,et al. Target Classification Using the Deep Convolutional Networks for SAR Images , 2016, IEEE Transactions on Geoscience and Remote Sensing.
[37] Hongwei Liu,et al. Convolutional Neural Network With Data Augmentation for SAR Target Recognition , 2016, IEEE Geoscience and Remote Sensing Letters.
[38] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[39] Simon Osindero,et al. Conditional Generative Adversarial Nets , 2014, ArXiv.
[40] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[41] Jing Wang,et al. Robust Face Recognition via Adaptive Sparse Representation , 2014, IEEE Transactions on Cybernetics.
[42] Hugh Griffiths,et al. Radar Automatic Target Recognition (ATR) and Non-Cooperative Target Recognition (NCTR) , 2013 .
[43] I. Hajnsek,et al. A tutorial on synthetic aperture radar , 2013, IEEE Geoscience and Remote Sensing Magazine.
[44] Yoshua Bengio,et al. Better Mixing via Deep Representations , 2012, ICML.
[45] Thomas S. Huang,et al. Multi-View Automatic Target Recognition using Joint Sparse Representation , 2012, IEEE Transactions on Aerospace and Electronic Systems.
[46] Karsten Schulz,et al. Coherent simulation of SAR images , 2009, Remote Sensing.
[47] Bir Bhanu,et al. Exploiting azimuthal variance of scatterers for multiple-look SAR recognition , 2002, SPIE Defense + Commercial Sensing.
[48] Michael Lee Bryant,et al. Standard SAR ATR evaluation experiments using the MSTAR public release data set , 1998, Defense, Security, and Sensing.
[49] Armin W. Doerry,et al. Synthetic Aperture Radar , 1992, Inverse Synthetic Aperture Radar Imaging with MATLAB® Algorithms.
[50] S. Lee,et al. Shooting and bouncing rays: calculating the RCS of an arbitrarily shaped cavity , 1989 .
[51] Chenwei Wang,et al. Multiview Attention CNN-LSTM Network for SAR Automatic Target Recognition , 2021, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[52] Jinsung Yoon,et al. GENERATIVE ADVERSARIAL NETS , 2018 .
[53] Stefan Auer,et al. 3D Synthetic Aperture Radar Simulation for Interpreting Complex Urban Reflection Scenarios , 2011 .