Zheng, C.[Chen],
Zhang, Y.[Yun],
Wang, L.G.[Lei-Guang],
Semantic Segmentation of Remote Sensing Imagery Using an Object-Based
Markov Random Field Model With Auxiliary Label Fields,
GeoRS(55), No. 5, May 2017, pp. 3015-3028.
IEEE DOI
1705
Markov processes, image segmentation, remote sensing,
auxiliary label field, hierarchical semantic information,
object-based MRF model, object-based Markov random field model,
probability distribution, remote sensing imagery,
remote sensing images, semantic segmentation, Context,
Context modeling, Image segmentation, Probability distribution,
Remote sensing, Semantics, Spatial resolution,
Auxiliary label field, object-based Markov random field,
remote sensing image, semantic, segmentation
BibRef
Zheng, C.[Chen],
Pan, X.X.[Xin-Xin],
Chen, X.H.[Xiao-Hui],
Yang, X.H.[Xiao-Hui],
Xin, X.[Xin],
Su, L.M.[Li-Min],
An Object-Based Markov Random Field Model with Anisotropic Penalty
for Semantic Segmentation of High Spatial Resolution Remote Sensing
Imagery,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Zhang, J.[Jing],
Lin, S.[Shaofu],
Ding, L.[Lei],
Bruzzone, L.[Lorenzo],
Multi-Scale Context Aggregation for Semantic Segmentation of Remote
Sensing Images,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Ding, L.,
Tang, H.,
Bruzzone, L.,
LANet: Local Attention Embedding to Improve the Semantic Segmentation
of Remote Sensing Images,
GeoRS(59), No. 1, January 2021, pp. 426-435.
IEEE DOI
2012
Semantics, Image segmentation, Feature extraction, Decoding,
Remote sensing, Correlation, Convolutional neural networks,
semantic segmentation
BibRef
Li, J.L.[Jing-Lun],
Xiu, J.P.[Jia-Peng],
Yang, Z.Q.[Zheng-Qiu],
Liu, C.[Chen],
Dual Path Attention Net for Remote Sensing Semantic Image
Segmentation,
IJGI(9), No. 10, 2020, pp. xx-yy.
DOI Link
2010
BibRef
Song, A.[Ahram],
Kim, Y.[Yongil],
Semantic Segmentation of Remote-Sensing Imagery Using Heterogeneous
Big Data: International Society for Photogrammetry and Remote Sensing
Potsdam and Cityscape Datasets,
IJGI(9), No. 10, 2020, pp. xx-yy.
DOI Link
2010
BibRef
Wang, J.X.[Jia-Xin],
Ding, C.H.Q.[Chris H. Q.],
Chen, S.B.[Si-Bao],
He, C.G.[Cheng-Gang],
Luo, B.[Bin],
Semi-Supervised Remote Sensing Image Semantic Segmentation via
Consistency Regularization and Average Update of Pseudo-Label,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Xu, Z.Y.[Zhi-Yong],
Zhang, W.C.[Wei-Cun],
Zhang, T.X.[Tian-Xiang],
Li, J.Y.[Jiang-Yun],
HRCNet: High-Resolution Context Extraction Network for Semantic
Segmentation of Remote Sensing Images,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Ouyang, S.[Song],
Li, Y.[Yansheng],
Combining Deep Semantic Segmentation Network and Graph Convolutional
Neural Network for Semantic Segmentation of Remote Sensing Imagery,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Chen, B.[Bingyu],
Xia, M.[Min],
Huang, J.Q.[Jun-Qing],
MFANet: A Multi-Level Feature Aggregation Network for Semantic
Segmentation of Land Cover,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Huang, J.Q.[Jun-Qing],
Weng, L.[Liguo],
Chen, B.[Bingyu],
Xia, M.[Min],
DFFAN: Dual Function Feature Aggregation Network for Semantic
Segmentation of Land Cover,
IJGI(10), No. 3, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Peng, J.[Jian],
Mei, X.M.[Xiao-Ming],
Li, W.[Wenbo],
Hong, L.[Liang],
Sun, B.[Bingyu],
Li, H.F.[Hai-Feng],
Scene Complexity: A New Perspective on Understanding the Scene
Semantics of Remote Sensing and Designing Image-Adaptive
Convolutional Neural Networks,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Zhang, C.[Cheng],
Jiang, W.S.[Wan-Shou],
Zhao, Q.[Qing],
Semantic Segmentation of Aerial Imagery via Split-Attention Networks
with Disentangled Nonlocal and Edge Supervision,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Liang, C.B.[Chen-Bin],
Cheng, B.[Bo],
Xiao, B.H.[Bai-Hua],
He, C.Q.[Chenlin-Qiu],
Liu, X.[Xunan],
Jia, N.[Ning],
Chen, J.[Jinfen],
Semi-/Weakly-Supervised Semantic Segmentation Method and Its
Application for Coastal Aquaculture Areas Based on Multi-Source
Remote Sensing Images: Taking the Fujian Coastal Area (Mainly Sanduo)
as an Example,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Chen, X.,
Li, Z.,
Jiang, J.,
Han, Z.,
Deng, S.,
Li, Z.,
Fang, T.,
Huo, H.,
Li, Q.,
Liu, M.,
Adaptive Effective Receptive Field Convolution for Semantic
Segmentation of VHR Remote Sensing Images,
GeoRS(59), No. 4, April 2021, pp. 3532-3546.
IEEE DOI
2104
Radio frequency, Convolution, Feature extraction,
Image segmentation, Semantics, Remote sensing, Shape, Field of view,
semantic contextual information
BibRef
Cui, W.[Wei],
He, X.[Xin],
Yao, M.[Meng],
Wang, Z.[Ziwei],
Hao, Y.J.[Yuan-Jie],
Li, J.[Jie],
Wu, W.J.[Wei-Jie],
Zhao, H.L.[Hui-Lin],
Xia, C.[Cong],
Li, J.[Jin],
Cui, W.Q.[Wen-Qi],
Knowledge and Spatial Pyramid Distance-Based Gated Graph Attention
Network for Remote Sensing Semantic Segmentation,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Inagaki, S.[Shun],
Imiya, A.[Atsushi],
Semantic Segmentation of Low Frame-Rate Image Sequence Using
Statistical Properties of Optical Flow for Remote Exploration,
ISVC14(I: 477-488).
Springer DOI
1501
BibRef
And:
Statistical Method for Semantic Segmentation of Dominant Plane from
Remote Exploration Image Sequence,
SSSPR14(263-272).
Springer DOI
1408
BibRef
Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Fua and Leclerc Guided Segmentation Papers .