DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides | Paper Citation Record

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This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence 39, 2481–2495.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides IEEE Transactions on Pattern Analysis and Machine Intelligence 39, 2481–2495

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This paper cites https://doi.org/10.1007/s10346-018-1092-z Yu, F., Koltun, V.,.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides https://doi.org/10.1007/s10346-018-1092-z Yu, F., Koltun, V.,

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This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 8

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This paper cites IEEE Trans.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides IEEE Trans

Reference 10

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides 3014–3017

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Unresolved cited work

Reference 13

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Unresolved cited work

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Unresolved cited work

Reference 20

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides 2261–2269

Reference 21

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This paper cites Geomorphology 86, 409–440.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Geomorphology 86, 409–440

Reference 23

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides 3027–3031

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This paper cites Pyramid Attention Network for Semantic Segmentation.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Pyramid Attention Network for Semantic Segmentation

Reference 29

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides GFF: Gated Fully Fusion for Semantic Segmentation

Reference 30

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Unresolved cited work

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This paper cites Procedia Computer Science 91, 566–575.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Procedia Computer Science 91, 566–575

Reference 32

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Reference 33

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This paper cites ISPRS Journal of Photogrammetry and Remote Sensing 135, 158–172.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides ISPRS Journal of Photogrammetry and Remote Sensing 135, 158–172

Reference 34

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This paper cites Remote Sensing of Environment 115, 1743–1757.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Remote Sensing of Environment 115, 1743–1757

Reference 37

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Unresolved cited work

Reference 38

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This paper cites Association for Computational Linguistics, Boulder, Colorado, pp.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Association for Computational Linguistics, Boulder, Colorado, pp

Reference 40

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This paper cites Attention U-Net: Learning Where to Look for the Pancreas.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Attention U-Net: Learning Where to Look for the Pancreas

Reference 41

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides 1717–1724

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This paper cites Bulletin of the Association of Engineering Geologists 21, 371–375.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Bulletin of the Association of Engineering Geologists 21, 371–375

Reference 43

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This paper cites IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9, 2868–2881.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9, 2868–2881

Reference 44

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Int J Comput Vis 115, 211–252

Reference 47

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Fully Convolutional Networks for Dense Semantic Labelling of High-Resolution Aerial Imagery

Reference 48

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Very Deep Convolutional Networks for Large-Scale Image Recognition

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides IEEE Geosci

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This paper cites URL http://www.sc.gov.cn/10462/12771/ 2017/8/14/10430678.shtml (accessed 8.14.19).

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides URL http://www.sc.gov.cn/10462/12771/ 2017/8/14/10430678.shtml (accessed 8.14.19)

Reference 52

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This paper cites IEEE Transactions on Geoscience and Remote Sensing 55, 881–893.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides IEEE Transactions on Geoscience and Remote Sensing 55, 881–893

Reference 54

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Landslides 16, 1551–1566

Reference 55

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Geoscience Frontiers 6, 825–836

Reference 57

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Reference 62

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Multi-Scale Context Aggregation by Dilated Convolutions

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Dilated Residual Networks, in IEEE Conference on Computer Vision and Pattern Recognition, pp

Reference 64

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides IEEE Transactions on Pattern Analysis and Machine Intelligence 40, 2109–2123

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides IEEE Geoscience and Remote Sensing Magazine 4, 22–40

Reference 68

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Reference 1158

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This paper cites GSA Bulletin 95, 406–421.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides GSA Bulletin 95, 406–421

Reference 1984

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This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence 8, 679–698.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides IEEE Transactions on Pattern Analysis and Machine Intelligence 8, 679–698

Reference 1986

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DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Nature 323, 533–536

Reference 1988

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Observation 99de52c0-2d43-43c9-909c-f392399dc00b · outbound

This paper cites International Journal of Remote Sensing 26, 1913–1926.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides International Journal of Remote Sensing 26, 1913–1926

Reference 2005

Resolution: verified exact; doi, observed 2026-08-14T10:36:38.922270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 26aa175f-2f57-4b9b-89df-b49bab7e59a2 · outbound

This paper cites International Journal of Remote Sensing 28, 1843–1856.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides International Journal of Remote Sensing 28, 1843–1856

Reference 2007

Resolution: verified exact; doi, observed 2026-08-14T10:36:39.348506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7a86ca80-0738-465d-8062-c2ce3324941e · outbound

This paper cites Engineering Geology 102, 112–131.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Engineering Geology 102, 112–131

Reference 2008

Resolution: verified exact; doi, observed 2026-08-14T10:36:38.850628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a629eb2a-c629-474d-9014-9540f130698a · outbound

This paper cites an unresolved cited work.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Unresolved cited work

Reference 2009

Resolution: verified exact; doi, observed 2026-08-14T10:36:39.060738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 55bf7b8c-1b98-4088-9036-327286b0e52d · outbound

This paper cites Geomorphology 116, 24–36.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Geomorphology 116, 24–36

Reference 2010

Resolution: verified exact; doi, observed 2026-08-14T10:36:38.979932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 67c5e50c-5238-4a67-b4fe-9afad9ca9023 · outbound

This paper cites Engineering Geology 122, 9–21.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Engineering Geology 122, 9–21

Reference 2011

Resolution: verified exact; doi, observed 2026-08-14T10:36:39.142239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a2f16806-c788-453c-afaf-0fb125c88a63 · outbound

This paper cites ISPRS Journal of Photogrammetry and Remote Sensing 67, 105–119.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides ISPRS Journal of Photogrammetry and Remote Sensing 67, 105–119

Reference 2012

Resolution: verified exact; doi, observed 2026-08-14T10:36:38.964590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 138a019d-5dc6-4bbd-86a8-e72be50bb6bf · outbound

This paper cites Nat Hazards 68, 1021–1039.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Nat Hazards 68, 1021–1039

Reference 2013

Resolution: verified exact; doi, observed 2026-08-14T10:36:39.105766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a3c327c1-f5e2-4e2c-83bc-6ef8a317f34e · outbound

This paper cites an unresolved cited work.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Unresolved cited work

Reference 2014

Resolution: verified exact; doi, observed 2026-08-14T10:36:39.332789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0c9285c6-3709-4703-8615-3fd2585b53f5 · outbound

This paper cites (Eds.), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015, Lecture Notes in Computer Science.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides (Eds.), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015, Lecture Notes in Computer Science

Reference 2015

Resolution: malformed identifier; no resolver link, observed 2026-08-14T10:36:38.627598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f804404-02cd-47f9-8e71-ad668bbf267a · outbound

This paper cites 1563–1572.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides 1563–1572

Reference 2016

Resolution: verified exact; raw_fallback, observed 2026-08-14T10:36:40.545782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 93a2cdee-32d3-4dc3-a8f8-7399ce356f96 · outbound

This paper cites an unresolved cited work.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Unresolved cited work

Reference 2017

Resolution: verified exact; doi, observed 2026-08-14T10:36:39.378554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ed2d275e-8758-41ab-9ac4-5cb987fc1dd4 · outbound

This paper cites Landslides 15, 967–983.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Landslides 15, 967–983

Reference 2018

Resolution: verified exact; doi, observed 2026-08-14T10:36:39.190660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0c16eeaf-e29b-4009-b53e-fb61f11a50ab · outbound

This paper cites Earth, Planets and Space 71,.

DFPENet-geology: A Deep Learning Framework for High Precision Recognition and Segmentation of Co-seismic Landslides Earth, Planets and Space 71,

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:36:40.685598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers