基于图像特征融合的遥感场景零样本分类算法 下载: 968次
吴晨, 王宏伟, 袁昱纬, 王志强, 刘宇, 程红, 全吉成. 基于图像特征融合的遥感场景零样本分类算法[J]. 光学学报, 2019, 39(6): 0610002.
Chen Wu, Hongwei Wang, Yuwei Yuan, Zhiqiang Wang, Yu Liu, Hong Cheng, Jicheng Quan. Image Feature Fusion Based Remote Sensing Scene Zero-Shot Classification Algorithm[J]. Acta Optica Sinica, 2019, 39(6): 0610002.
[1] 刘大伟, 韩玲, 韩晓勇. 基于深度学习的高分辨率遥感影像分类研究[J]. 光学学报, 2016, 36(4): 0428001.
刘大伟, 韩玲, 韩晓勇. 基于深度学习的高分辨率遥感影像分类研究[J]. 光学学报, 2016, 36(4): 0428001.
[5] Xian YQ, AkataZ, SharmaG, et al. Latent embeddings for zero-shot classification[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 2016: 69- 77.
Xian YQ, AkataZ, SharmaG, et al. Latent embeddings for zero-shot classification[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 2016: 69- 77.
[6] WangD, LiY, LinY, et al.Relational knowledge transfer for zero-shot learning[C]∥Thirtieth AAAI Conference in Artificial Intelligence, February 12-17, 2016, Phoenix, Arizona, USA.California: AAAI Press, 2016: 2145- 2151.
WangD, LiY, LinY, et al.Relational knowledge transfer for zero-shot learning[C]∥Thirtieth AAAI Conference in Artificial Intelligence, February 12-17, 2016, Phoenix, Arizona, USA.California: AAAI Press, 2016: 2145- 2151.
[7] Zhang ZM, SaligramaV. Zero-shot learning via joint latent similarity embedding[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 2016: 6034- 6042.
Zhang ZM, SaligramaV. Zero-shot learning via joint latent similarity embedding[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 2016: 6034- 6042.
[8] Zhang ZM, SaligramaV. Zero-shot learning via semantic similarity embedding[C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 2015: 4166- 4174.
Zhang ZM, SaligramaV. Zero-shot learning via semantic similarity embedding[C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 2015: 4166- 4174.
[10] Li YN, Wang DH, Hu HH, et al. Zero-shot recognition using dual visual-semantic mapping paths[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2017: 5207- 5215.
Li YN, Wang DH, Hu HH, et al. Zero-shot recognition using dual visual-semantic mapping paths[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2017: 5207- 5215.
[11] KodirovE, XiangT, Gong SG. Semantic autoencoder for zero-shot learning[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2017: 4447- 4456.
KodirovE, XiangT, Gong SG. Semantic autoencoder for zero-shot learning[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2017: 4447- 4456.
[12] FernandoB, FromontE, MuseletD, et al. Discriminative feature fusion for image classification[C]∥2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 16-21, 2012, Providence, RI, USA. New York: IEEE, 2012: 3434- 3441.
FernandoB, FromontE, MuseletD, et al. Discriminative feature fusion for image classification[C]∥2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 16-21, 2012, Providence, RI, USA. New York: IEEE, 2012: 3434- 3441.
[18] Swain M J, Ballard D H. Color indexing[J]. International Journal of Computer Vision, 1991, 7(1): 11-32.
Swain M J, Ballard D H. Color indexing[J]. International Journal of Computer Vision, 1991, 7(1): 11-32.
[22] YangY, NewsamS. Bag-of-visual-words and spatial extensions for land-use classification[C]∥Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems, November 2-5, 2010, San Jose, California. New York: ACM, 2010: 270- 279.
YangY, NewsamS. Bag-of-visual-words and spatial extensions for land-use classification[C]∥Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems, November 2-5, 2010, San Jose, California. New York: ACM, 2010: 270- 279.
[23] PerronninF, SánchezJ, MensinkT. Improving the fisher kernel for large-scale image classification[M] ∥Daniilidis K, Maragos P, Paragios N. Computer Vision-ECCV 2010. Berlin, Heidelberg: Springer, 2010: 143- 156.
PerronninF, SánchezJ, MensinkT. Improving the fisher kernel for large-scale image classification[M] ∥Daniilidis K, Maragos P, Paragios N. Computer Vision-ECCV 2010. Berlin, Heidelberg: Springer, 2010: 143- 156.
[24] Blei D M, Ng A Y, Jordan M I. Latent dirichl location[J]. Journal of Machine Learning research, 2003, 3: 993-1022.
Blei D M, Ng A Y, Jordan M I. Latent dirichl location[J]. Journal of Machine Learning research, 2003, 3: 993-1022.
[25] Jia YQ, ShelhamerE, DonahueJ, et al. Caffe: convolutional architecture for fast feature embedding[C]∥Proceedings of the 22nd ACM international conference on Multimedia, November 3-7, 2014, Orlando, Florida, USA. New York: ACM, 2014: 675- 678.
Jia YQ, ShelhamerE, DonahueJ, et al. Caffe: convolutional architecture for fast feature embedding[C]∥Proceedings of the 22nd ACM international conference on Multimedia, November 3-7, 2014, Orlando, Florida, USA. New York: ACM, 2014: 675- 678.
[26] SimonyanK, Zisserman A. Very deep convolutional networks for large-scale image recognition[EB/OL]. ( 2015-04-10)[2018-12-25]. https: ∥arxiv.org/abs/1409. 1556.
SimonyanK, Zisserman A. Very deep convolutional networks for large-scale image recognition[EB/OL]. ( 2015-04-10)[2018-12-25]. https: ∥arxiv.org/abs/1409. 1556.
[27] SzegedyC, LiuW, Jia YQ, et al. Going deeper with convolutions[C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 2015: 1- 9.
SzegedyC, LiuW, Jia YQ, et al. Going deeper with convolutions[C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 2015: 1- 9.
[28] He KM, Zhang XY, Ren SQ, et al. Deep residual learning for image recognition[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 2016: 770- 778.
He KM, Zhang XY, Ren SQ, et al. Deep residual learning for image recognition[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 2016: 770- 778.
[29] Wang JJ, Yang JC, YuK, et al. Locality-constrained linear coding for image classification[C]∥2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), June 13-18, 2010, San Francisco, CA, USA. New York: IEEE, 2010: 3360- 3367.
Wang JJ, Yang JC, YuK, et al. Locality-constrained linear coding for image classification[C]∥2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), June 13-18, 2010, San Francisco, CA, USA. New York: IEEE, 2010: 3360- 3367.
[30] BoschA, ZissermanA, MuñozX. Scene classification via pLSA[M] ∥Leonardis A, Bischof H, Pinz A. Computer Vision-ECCV 2006. Berlin, Heidelberg: Springer, 2006: 517- 530.
BoschA, ZissermanA, MuñozX. Scene classification via pLSA[M] ∥Leonardis A, Bischof H, Pinz A. Computer Vision-ECCV 2006. Berlin, Heidelberg: Springer, 2006: 517- 530.
[31] LazebnikS, SchmidC, PonceJ. Beyond bags of features: spatial pyramid matching for recognizing natural scene categories[C]∥2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), June 17-22, 2006, New York, USA. New York: IEEE, 2006: 2169- 2178.
LazebnikS, SchmidC, PonceJ. Beyond bags of features: spatial pyramid matching for recognizing natural scene categories[C]∥2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), June 17-22, 2006, New York, USA. New York: IEEE, 2006: 2169- 2178.
[33] RupnikJ, Shawe-TaylorJ. Multi-view canonical correlation analysis[C]∥Proceedings of the 13th Multiconference on Information Society, IS, Ljubljana, Slovenia. [S.l.: s.n.], 2010: 201- 204.
RupnikJ, Shawe-TaylorJ. Multi-view canonical correlation analysis[C]∥Proceedings of the 13th Multiconference on Information Society, IS, Ljubljana, Slovenia. [S.l.: s.n.], 2010: 201- 204.
吴晨, 王宏伟, 袁昱纬, 王志强, 刘宇, 程红, 全吉成. 基于图像特征融合的遥感场景零样本分类算法[J]. 光学学报, 2019, 39(6): 0610002. Chen Wu, Hongwei Wang, Yuwei Yuan, Zhiqiang Wang, Yu Liu, Hong Cheng, Jicheng Quan. Image Feature Fusion Based Remote Sensing Scene Zero-Shot Classification Algorithm[J]. Acta Optica Sinica, 2019, 39(6): 0610002.