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2006
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Elsevier DOI
2009
Deep learning, Convolutional neural network, Land cover, Aerial imagery
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2009
Raster to properties.
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Tran, B.H.[Ba-Huy],
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Elsevier DOI
2011
Object-based image analysis, Curve matching, His-Cov,
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Chen, J.D.[Jing-Dong],
Zhou, Y.[Yanan],
Sun, Y.W.[Ying-Wei],
Shen, Z.F.[Zhan-Feng],
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Farmland Parcel Mapping in Mountain Areas Using Time-Series SAR Data
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2011
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Shivappriya, S.N.,
Priyadarsini, M.J.P.[M. Jasmine Pemeena],
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Puttamadappa, C.,
Parameshachari, B.D.,
Cascade Object Detection and Remote Sensing Object Detection Method
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2101
BibRef
Cao, Z.Y.[Zhi-Ying],
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Yan, M.L.[Meng-Long],
Fu, K.[Kun],
C3Net: Cross-Modal Feature Recalibrated, Cross-Scale Semantic
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2102
BibRef
Zhang, W.[Wei],
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2102
BibRef
Qu, L.[Le'an],
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2102
BibRef
Li, X.R.[Xing-Rong],
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Zhang, Q.[Qing],
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2103
BibRef
Gilcher, M.[Mario],
Udelhoven, T.[Thomas],
Field Geometry and the Spatial and Temporal Generalization of Crop
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2103
BibRef
Taravat, A.[Alireza],
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Advanced Fully Convolutional Networks for Agricultural Field Boundary
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2103
BibRef
Luo, C.[Chong],
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Shao, Y.Q.[Yi-Qun],
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DOI Link
2103
BibRef
Xue, Y.A.[Yong-An],
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DOI Link
2103
BibRef
Hong, R.[Rokgi],
Park, J.[Jinseok],
Jang, S.J.[Seong-Ju],
Shin, H.J.[Hyung-Jin],
Kim, H.[Hakkwan],
Song, I.[Inhong],
Development of a Parcel-Level Land Boundary Extraction Algorithm for
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DOI Link
2104
BibRef
Li, W.[Wei],
Wei, W.[Wei],
Zhang, L.[Lei],
GSDet: Object Detection in Aerial Images Based on Scale Reasoning,
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IEEE DOI
2105
Object detection, Feature extraction, Proposals, Convolution,
Knowledge engineering, Detectors, Cognition, Object detection,
reasoning
BibRef
Waldner, F.[François],
Diakogiannis, F.I.[Foivos I.],
Batchelor, K.[Kathryn],
Ciccotosto-Camp, M.[Michael],
Cooper-Williams, E.[Elizabeth],
Herrmann, C.[Chris],
Mata, G.[Gonzalo],
Toovey, A.[Andrew],
Detect, Consolidate, Delineate: Scalable Mapping of Field Boundaries
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DOI Link
2106
BibRef
Yang, C.[Chun],
Rottensteiner, F.[Franz],
Heipke, C.[Christian],
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Elsevier DOI
2106
Hierarchical consistent land use classification, CNN,
Geospatial database, Aerial imagery
BibRef
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Hu, S.[Shougeng],
Li, W.D.[Wei-Dong],
Zhang, C.R.[Chuan-Rong],
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Improving Parcel-Level Mapping of Smallholder Crops from VHSR
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RS(13), No. 11, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Tassi, A.[Andrea],
Gigante, D.[Daniela],
Modica, G.[Giuseppe],
di Martino, L.[Luciano],
Vizzari, M.[Marco],
Pixel- vs. Object-Based Landsat 8 Data Classification in Google Earth
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RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Wei, Z.H.[Zhong-Hui],
Gu, X.H.[Xiao-He],
Sun, Q.[Qian],
Hu, X.Q.[Xue-Qian],
Gao, Y.B.[Yun-Bing],
Analysis of the Spatial and Temporal Pattern of Changes in Abandoned
Farmland Based on Long Time Series of Remote Sensing Data,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Dong, R.[Ruchan],
Jiao, L.C.[Li-Cheng],
Zhang, Y.[Yan],
Zhao, J.[Jin],
Shen, W.Y.[Wei-Yan],
A Multi-Scale Spatial Attention Region Proposal Network for
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RS(13), No. 17, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Xu, Z.Y.[Zhi-Yong],
Zhang, W.C.[Wei-Cun],
Zhang, T.X.[Tian-Xiang],
Yang, Z.F.[Zhi-Fang],
Li, J.Y.[Jiang-Yun],
Efficient Transformer for Remote Sensing Image Segmentation,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Wang, H.[Hong],
Chen, X.Z.[Xian-Zhong],
Zhang, T.X.[Tian-Xiang],
Xu, Z.Y.[Zhi-Yong],
Li, J.Y.[Jiang-Yun],
CCTNet: Coupled CNN and Transformer Network for Crop Segmentation of
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RS(14), No. 9, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Cheng, X.[Xu],
Liu, L.H.[Li-Hua],
Song, C.[Chen],
A Cyclic Information-Interaction Model for Remote Sensing Image
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RS(13), No. 19, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Torres, R.N.[Rocio Nahime],
Fraternali, P.[Piero],
Learning to Identify Illegal Landfills through Scene Classification
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RS(13), No. 22, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Pare, S.[Shreya],
Mittal, H.[Himanshu],
Sajid, M.[Mohammad],
Bansal, J.C.[Jagdish Chand],
Saxena, A.[Amit],
Jan, T.[Tony],
Pedrycz, W.[Witold],
Prasad, M.[Mukesh],
Remote Sensing Imagery Segmentation: A Hybrid Approach,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Wang, G.Q.[Guan-Qun],
Zhuang, Y.[Yin],
Chen, H.[He],
Liu, X.[Xiang],
Zhang, T.[Tong],
Li, L.L.[Lian-Lin],
Dong, S.[Shan],
Sang, Q.B.[Qian-Bo],
FSoD-Net: Full-Scale Object Detection From Optical Remote Sensing
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IEEE DOI
2112
Object detection, Remote sensing, Optical imaging,
Feature extraction, Detectors, Optical detectors,
optical remote sensing
BibRef
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Esau, T.J.[Travis J.],
Farooque, A.A.[Aitazaz A.],
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Heung, B.[Brandon],
Estimation of Agricultural Dykelands Cultivated in Nova Scotia Using
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DOI Link
2112
BibRef
Brauchler, M.[Melanie],
Stoffels, J.[Johannes],
Nink, S.[Sascha],
Extension of an Open GEOBIA Framework for Spatially Explicit Forest
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RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Wen, C.[Caiyun],
Lu, M.[Miao],
Bi, Y.[Ying],
Zhang, S.N.[Sheng-Nan],
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Zhou, Q.[Qingbo],
Wu, W.B.[Wen-Bin],
An Object-Based Genetic Programming Approach for Cropland Field
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RS(14), No. 5, 2022, pp. xx-yy.
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2203
BibRef
Li, T.[Ting],
Johansen, K.[Kasper],
McCabe, M.F.[Matthew F.],
A machine learning approach for identifying and delineating
agricultural fields and their multi-temporal dynamics using three
decades of Landsat data,
PandRS(186), 2022, pp. 83-101.
Elsevier DOI
2203
Center-pivot field, Delineation, DBSCAN,
Convolution neural networks, Spectral clustering, Random forest
BibRef
Lu, R.[Rui],
Wang, N.[Nan],
Zhang, Y.B.[Yan-Bin],
Lin, Y.N.[Ye-Neng],
Wu, W.Q.[Wen-Qiang],
Shi, Z.[Zhou],
Extraction of Agricultural Fields via DASFNet with Dual Attention
Mechanism and Multi-scale Feature Fusion in South Xinjiang, China,
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DOI Link
2205
BibRef
Vizzari, M.[Marco],
PlanetScope, Sentinel-2, and Sentinel-1 Data Integration for
Object-Based Land Cover Classification in Google Earth Engine,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Gonçalves, V.P.[Vinicius Paiva],
Ribeiro, E.A.W.[Eduardo Augusto Werneck],
Imai, N.N.[Nilton Nobuhiro],
Mapping Areas Invaded by Pinus sp. from Geographic Object-Based Image
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RS(14), No. 12, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Mei, W.Y.[Wei-Ye],
Wang, H.Y.[Hao-Yu],
Fouhey, D.[David],
Zhou, W.Q.[Wei-Qi],
Hinks, I.[Isabella],
Gray, J.M.[Josh M.],
van Berkel, D.[Derek],
Jain, M.[Meha],
Using Deep Learning and Very-High-Resolution Imagery to Map
Smallholder Field Boundaries,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Cai, Z.W.[Zhi-Wen],
Hu, Q.[Qiong],
Zhang, X.Y.[Xin-Yu],
Yang, J.Y.[Jing-Ya],
Wei, H.D.[Hao-Dong],
He, Z.[Zhen],
Song, Q.[Qian],
Wang, C.[Cong],
Yin, G.F.[Gao-Fei],
Xu, B.D.[Bao-Dong],
An Adaptive Image Segmentation Method with Automatic Selection of
Optimal Scale for Extracting Cropland Parcels in Smallholder Farming
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RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Zhang, Z.Q.[Zhi-Qi],
Lu, W.[Wen],
Cao, J.S.[Jin-Shan],
Xie, G.Q.[Guang-Qi],
MKANet: An Efficient Network with Sobel Boundary Loss for Land-Cover
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RS(14), No. 18, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Wang, S.[Sherrie],
Waldner, F.[François],
Lobell, D.B.[David B.],
Unlocking Large-Scale Crop Field Delineation in Smallholder Farming
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RS(14), No. 22, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Muhammad, U.[Usman],
Hoque, M.Z.[Md Ziaul],
Wang, W.Q.[Wei-Qiang],
Oussalah, M.[Mourad],
Patch-Based Discriminative Learning for Remote Sensing Scene
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RS(14), No. 23, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Xing, H.Q.[Hua-Qiao],
Chen, B.Y.[Bing-Yao],
Lu, M.[Miao],
A Sub-Seasonal Crop Information Identification Framework for Crop
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Sentinel-2 Imagery,
RS(14), No. 24, 2022, pp. xx-yy.
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2212
BibRef
Jiao, S.[Shuhui],
Shen, Z.F.[Zhan-Feng],
Kou, W.Q.[Wen-Qi],
Wang, H.Y.[Hao-Yu],
Li, J.L.[Jun-Li],
Jiao, Z.H.[Zhi-Hao],
Lei, Y.T.[Ya-Ting],
Parcel-Level Mapping of Horticultural Crops in Mountain Areas Using
Irregular Time Series and VHR Images Taking Qixia, China as An
Example,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link
2301
BibRef
Liu, L.R.[Li-Rong],
Tang, X.M.[Xin-Ming],
Gan, Y.H.[Yu-Hang],
You, S.C.[Shu-Cheng],
Luo, Z.Y.[Zheng-Yu],
Du, L.[Lei],
He, Y.[Yun],
Research on Optimization of Processing Parcels of New Bare Land Based
on Remote Sensing Image Change Detection,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link
2301
BibRef
Gu, L.Y.[Ling-Yun],
Fang, Q.Y.[Qing-Yun],
Wang, Z.[Zhaokui],
Popov, E.[Eugene],
Dong, G.[Ge],
Learning Lightweight and Superior Detectors with Feature Distillation
for Onboard Remote Sensing Object Detection,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link
2301
BibRef
Ozturk, M.Y.,
Colkesen, I.,
Evaluation of Effectiveness of Patch Based Image Classification
Technique Using High Resolution Worldview-2 Image,
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DOI Link
2201
BibRef
McLaughlin, C.[Connor],
Woodley, A.[Alan],
Geva, S.[Shlomo],
Chappell, T.[Timothy],
Kelly, W.[Wayne],
Boles, W.[Wageeh],
de Vine, L.[Lance],
Hutson, H.[Holly],
Object Based Remote Sensing Using Sentinel Data,
DICTA20(1-7)
IEEE DOI
2201
Earth, Image analysis, Satellites, Digital images,
Vegetation mapping, Australia, Remote sensing, remote sensing,
object-based image analysis
BibRef
Innani, S.[Shubham],
Dutande, P.[Prasad],
Baheti, B.[Bhakti],
Talbar, S.[Sanjay],
Baid, U.[Ujjwal],
Fuse-PN: A Novel Architecture for Anomaly Pattern Segmentation in
Aerial Agricultural Images,
AgriVision21(2954-2962)
IEEE DOI
2109
Deep learning, Training, Image segmentation,
Semantics, Data integration, Computer architecture
BibRef
Chen, T.,
Wang, H.,
Liu, H.,
Du, J.,
Wu, P.,
An Island Remote Sensing Image Segmentation Algorithm Based on
FC_U-Net Network,
CVIDL20(100-105)
IEEE DOI
2102
convolutional neural nets, geophysical image processing,
image classification, image segmentation, Features fusion
BibRef
Meyer, L.,
Lemarchand, F.,
Sidiropoulos, P.,
A Deep Learning Architecture for Batch-mode Fully Automated Field
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2012
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Gujrathi, A.,
Yang, C.,
Rottensteiner, F.,
Buddhiraju, K.M.,
Heipke, C.,
Improving the Classification of Land Use Objects Using Dense
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DOI Link
2012
BibRef
Zheng, Z.[Zhe],
Lei, L.[Lin],
Sun, H.[Hao],
Kuang, G.Y.[Gang-Yao],
A Review of Remote Sensing Image Object Detection Algorithms Based on
Deep Learning,
ICIVC20(34-43)
IEEE DOI
2009
Object detection, Remote sensing, Machine learning,
Feature extraction, Convolutional neural networks,
Convolutional neural networks
BibRef
Li, C.,
Yang, T.,
Zhu, S.,
Chen, C.,
Guan, S.,
Density Map Guided Object Detection in Aerial Images,
EarthVision20(737-746)
IEEE DOI
2008
Agriculture, Object detection, Detectors,
Proposals, Task analysis, Image resolution
BibRef
Sheng, H.,
Chen, X.,
Su, J.,
Rajagopal, R.,
Ng, A.,
Effective Data Fusion with Generalized Vegetation Index:
Evidence from Land Cover Segmentation in Agriculture,
AgriVision20(267-276)
IEEE DOI
2008
Vegetation mapping, Indexes, Remote sensing, Data integration,
Agriculture, Soil, Satellites
BibRef
Aung, H.L.,
Uzkent, B.,
Burke, M.,
Lobell, D.,
Ermon, S.,
Farm Parcel Delineation Using Spatio-temporal Convolutional Networks,
AgriVision20(340-349)
IEEE DOI
2008
Satellites, Task analysis, Image segmentation, Meteorology,
Machine learning, Computer science
BibRef
Michaelsen, E.,
Meidow, J.,
Design of Orientation Assessment Functions for Gestalt-grouping
Utilizing Labeled Sample-data,
PIA19(169-173).
DOI Link
1912
BibRef
Bosch, M.,
Christie, G.,
Gifford, C.,
Sensor Adaptation for Improved Semantic Segmentation of Overhead
Imagery,
WACV19(648-656)
IEEE DOI
1904
image segmentation, learning (artificial intelligence),
neural nets, object detection, semantic networks,
Training data
BibRef
Zhang, Q.Q.[Qian-Qian],
Liu, Y.Z.[Ya-Zhou],
Sun, Q.S.[Quan-Sen],
Object Classification of Remote Sensing Images Based on Optimized
Projection Supervised Discrete Hashing,
ICPR21(9507-9513)
IEEE DOI
2105
Learning systems, Hash functions, Image processing,
Memory management, Pattern recognition,
object classification
BibRef
Kang, T.,
Liu, Y.Z.[Ya-Zhou],
Sun, Q.S.[Quan-Sen],
Object Classification of Remote Sensing Images Based on Partial
Randomness Supervised Discrete Hashing,
ICPR18(1935-1940)
IEEE DOI
1812
Remote sensing, Binary codes, Linear programming, Training data,
Training, Optimization, Semantics, object classification, partial randomness
BibRef
Tian, C.,
Li, C.,
Shi, J.,
Dense Fusion Classmate Network for Land Cover Classification,
DeepGlobe18(262-2624)
IEEE DOI
1812
Roads, Image segmentation, Semantics, Task analysis, Training,
Convolution, Satellites
BibRef
Samy, M.,
Amer, K.,
Eissa, K.,
Shaker, M.,
ElHelw, M.,
NU-Net: Deep Residual Wide Field of View Convolutional Neural Network
for Semantic Segmentation,
DeepGlobe18(267-2674)
IEEE DOI
1812
Image segmentation, Semantics, Roads,
Convolution, Pattern recognition
BibRef
Seferbekov, S.,
Iglovikov, V.,
Buslaev, A.,
Shvets, A.,
Feature Pyramid Network for Multi-class Land Segmentation,
DeepGlobe18(272-2723)
IEEE DOI
1812
Image segmentation, Satellites, Training, Feature extraction,
Convolution, Semantics
BibRef
Pascual, G.,
Segui, S.,
Vitria, J.,
Uncertainty Gated Network for Land Cover Segmentation,
DeepGlobe18(276-2763)
IEEE DOI
1812
Uncertainty, Image segmentation, Logic gates, Semantics,
Measurement uncertainty, Image resolution
BibRef
Kuo, T.,
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Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Subpixel Target, Subpixel Land Use, Tiny Objects .