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Paper Citation Record · LEDGER

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping

As of 22 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 0 inbound Pith citation observations for arXiv:2501.03360.

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pith.paper-citation-record.v1
2501.03360 v1

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measured 66 of 66 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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A source-named dated measurement, never combined with another source.

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Reference resolution

66 of 66 outbound references displayed

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External citation measurements

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Outbound references

Observation 83121612-8f94-4466-98fe-8dcce852a7bf · outbound

This paper cites Estimating mangrove tree biomass and carbon con- tent: A comparison of forest inventory techniques and drone imagery,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Estimating mangrove tree biomass and carbon con- tent: A comparison of forest inventory techniques and drone imagery,

Reference 1

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Observation 4ad9c605-9a7b-433d-ab69-36be570e7404 · outbound

This paper cites Nellemann and E.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Nellemann and E

Reference 2

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Observation d8794fbf-5dfa-49ae-8865-27feebfe55b0 · outbound

This paper cites Mangrove roots model suggest an optimal porosity to prevent erosion,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Mangrove roots model suggest an optimal porosity to prevent erosion,

Reference 3

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Observation 48535b09-32c9-4939-8b65-d64317a1e9e9 · outbound

This paper cites Global economic potential for reducing carbon dioxide emissions from mangrove loss,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Global economic potential for reducing carbon dioxide emissions from mangrove loss,

Reference 4

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Observation 7a735fd9-2674-4d10-b6ab-6d95dd4fc4d8 · outbound

This paper cites Mangrove management for climate change adaptation and sus- tainable development in coastal zones,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Mangrove management for climate change adaptation and sus- tainable development in coastal zones,

Reference 5

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Observation a59bd55a-d2a5-4467-9492-30b1284cb791 · outbound

This paper cites Impact of mangrove forests degradation on biodiversity and ecosystem functioning,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Impact of mangrove forests degradation on biodiversity and ecosystem functioning,

Reference 6

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Observation 5b40c513-f1fe-453d-9208-65798e428959 · outbound

This paper cites Global potential and limits of mangrove blue carbon for climate change miti- gation,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Global potential and limits of mangrove blue carbon for climate change miti- gation,

Reference 7

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Observation 671a3e06-e2b8-4d29-9833-b5680e88accf · outbound

This paper cites Estimating and mapping mangrove biomass dynamic change using WorldView-2 images and digital surface models,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Estimating and mapping mangrove biomass dynamic change using WorldView-2 images and digital surface models,

Reference 8

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Observation c36f9f58-5006-4702-81ae-dfc908eababd · outbound

This paper cites Mapping mangrove using a red-edge mangrove index (REMI) based on Sentinel-2 multispectral images,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Mapping mangrove using a red-edge mangrove index (REMI) based on Sentinel-2 multispectral images,

Reference 9

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Observation c6686b9c-5d36-4b39-925e-e2a2ffbf8b0d · outbound

This paper cites A comparison of Gaofen-2 and Sentinel-2 imagery for mapping mangrove forests using object-oriented analysis and random forest,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping A comparison of Gaofen-2 and Sentinel-2 imagery for mapping mangrove forests using object-oriented analysis and random forest,

Reference 10

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Observation cd436bbd-f692-413e-b283-05897be3f972 · outbound

This paper cites Hyperspectral remote sensing data analysis and future challenges,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Hyperspectral remote sensing data analysis and future challenges,

Reference 11

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Observation 80922108-76e4-4c3b-8613-9853dd852188 · outbound

This paper cites Modern trends in hyperspectral image analysis: A review,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Modern trends in hyperspectral image analysis: A review,

Reference 12

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This paper cites All-addition hyperspectral compressed sensing for metasurface-driven miniaturized satellite,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping All-addition hyperspectral compressed sensing for metasurface-driven miniaturized satellite,

Reference 13

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Observation 28db15e9-6e7b-47ca-9bb3-6c6223d6a050 · outbound

This paper cites Signal subspace identification for incom- plete hyperspectral image with applications to various inverse problems,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Signal subspace identification for incom- plete hyperspectral image with applications to various inverse problems,

Reference 14

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Observation 6d2eab70-581d-4a36-a611-518965afa5ae · outbound

This paper cites Graph convolutional networks for hyperspectral image classification,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Graph convolutional networks for hyperspectral image classification,

Reference 15

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Observation 90e49b6c-d5f8-4e87-91f6-6fce937dd546 · outbound

This paper cites Hyperspectral change detection based on multiple morphological profiles,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Hyperspectral change detection based on multiple morphological profiles,

Reference 16

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Observation 50de55c8-aa85-4f1e-b6bc-08376eb7490c · outbound

This paper cites Hyperspectral change detection using semi- supervised graph neural network and convex deep learning,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Hyperspectral change detection using semi- supervised graph neural network and convex deep learning,

Reference 17

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Observation 9b518e51-35e8-41c3-9206-2d9e9bc220a9 · outbound

This paper cites Mapping invasive aquatic vegetation in the Sacramento- San Joaquin Delta using hyperspectral imagery,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Mapping invasive aquatic vegetation in the Sacramento- San Joaquin Delta using hyperspectral imagery,

Reference 18

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Observation 8d3e8736-1d89-4e84-b5ea-11c63ff8208a · outbound

This paper cites CODE-MM: Convex deep mangrove mapping algorithm based on optical satellite images,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping CODE-MM: Convex deep mangrove mapping algorithm based on optical satellite images,

Reference 19

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This paper cites Hyperspectral tensor completion using low-rank modeling and convex functional analysis,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Hyperspectral tensor completion using low-rank modeling and convex functional analysis,

Reference 20

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Observation 3d3083b4-f31d-4701-bd6e-f6e650277485 · outbound

This paper cites HyperQUEEN: Hyperspectral quantum deep network for image restoration,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping HyperQUEEN: Hyperspectral quantum deep network for image restoration,

Reference 21

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Observation f70e5b8a-de20-4818-acc2-34d7c4d13b85 · outbound

This paper cites Transformer-driven inverse problem transform for fast blind hyperspectral image dehazing,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Transformer-driven inverse problem transform for fast blind hyperspectral image dehazing,

Reference 22

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Observation ea147683-5a8b-46fc-bb2d-e39c0e773cd9 · outbound

This paper cites Remote sensing of mangrove ecosystems: A review,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Remote sensing of mangrove ecosystems: A review,

Reference 23

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Observation cfbeaa2f-fa4c-42d3-b6b3-a74721e9349b · outbound

This paper cites Remote sensing techniques for mangrove mapping,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Remote sensing techniques for mangrove mapping,

Reference 24

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Observation 0bc492ac-e41b-4417-b285-f5d079c8cd67 · outbound

This paper cites Maximum volume inscribed ellipsoid: A new simplex-structured matrix factoriza- tion framework via facet enumeration and convex optimization,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Maximum volume inscribed ellipsoid: A new simplex-structured matrix factoriza- tion framework via facet enumeration and convex optimization,

Reference 25

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This paper cites Sentinel-2: ESA’s optical high- resolution mission for GMES operational services,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Sentinel-2: ESA’s optical high- resolution mission for GMES operational services,

Reference 26

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Observation 580a836c-31c1-459a-8d7a-978d3f2dc343 · outbound

This paper cites Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping,

Reference 27

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Observation ffe62592-39f8-49ae-b086-27b3537d9ed2 · outbound

This paper cites Deep convolutional neural net- work for mangrove mapping,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Deep convolutional neural net- work for mangrove mapping,

Reference 28

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Observation d70f4a70-722b-402c-a0db-a68b9f0b42ed · outbound

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Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Theory of the backpropagation neural network,

Reference 29

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Observation 697808f0-7ef6-4bd3-8ac1-662a1fcbf032 · outbound

This paper cites Remote sensing techniques: Mapping and monitoring of mangrove ecosystem—A review,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Remote sensing techniques: Mapping and monitoring of mangrove ecosystem—A review,

Reference 30

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Observation e0c59cc8-9407-487a-8a5a-1cb90589a270 · outbound

This paper cites A soil-adjusted vegetation index (SA VI),.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping A soil-adjusted vegetation index (SA VI),

Reference 31

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Observation a92caadd-7394-442f-b75b-03f16533ecea · outbound

This paper cites Overview of the radiometric and biophysical performance of the MODIS vegetation indices,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Overview of the radiometric and biophysical performance of the MODIS vegetation indices,

Reference 32

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Observation 7995c108-dd30-4981-b8dd-12ed7ea166cb · outbound

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Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Red and photographic infrared linear combinations for monitoring vegetation,

Reference 33

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Observation 46c8c0a1-53ba-49e0-8765-5fb030b781ec · outbound

This paper cites Brazilian mangrove status: Three decades of satellite data analysis,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Brazilian mangrove status: Three decades of satellite data analysis,

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.561045Z digest=sha256:3b35909d694ef8a106516c9bc705d7a28014d8538562c5151348c525713b1de5

Observation 437c0950-bd19-4315-8763-2f72f032592d · outbound

This paper cites Modification of normalized difference water index (NDWI) to enhance open water features in remotely sensed imagery,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Modification of normalized difference water index (NDWI) to enhance open water features in remotely sensed imagery,

Reference 35

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raw_fallback, observed 2026-08-10T21:57:19.375860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.568544Z digest=sha256:793b02ed123ff5d739383ea0a08d4311071dd1f0acb418d0052da1f78df455a6

Observation 2966f5d9-c2a7-412c-95ca-8c269117a5d1 · outbound

This paper cites Enhanced mangrove vegetation index based on hyperspectral images for mapping mangrove,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Enhanced mangrove vegetation index based on hyperspectral images for mapping mangrove,

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.355493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.575091Z digest=sha256:acbd3b6252d92472755b7ad48492fe12801b4d0e4bfc6b9cfa33652f219ca37e

Observation a7e88554-10ed-487f-8d54-5909a248e7e9 · outbound

This paper cites Identifying mangroves through knowledge extracted from trained random forest models: An interpretable mangrove mapping approach (IMMA),.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Identifying mangroves through knowledge extracted from trained random forest models: An interpretable mangrove mapping approach (IMMA),

Reference 37

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raw_fallback, observed 2026-08-10T21:57:19.338873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.581076Z digest=sha256:3673d1a3a78caf924f592cbe05374087de011d33426148d5248afb47a36fe70d

Observation 0f094a67-0c06-4011-aa24-71509d9710a5 · outbound

This paper cites GC-UNet: An improved UNet model for mangrove segmentation using Landsat8,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping GC-UNet: An improved UNet model for mangrove segmentation using Landsat8,

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.321661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.586721Z digest=sha256:439ee004c621584bb2b096696dbf47d87ae93e88e7366827ff0cbc33d43513d2

Observation 2b7c8eba-b000-428d-a713-291a9e072e38 · outbound

This paper cites U-Net: Convolutional net- works for biomedical image segmentation,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping U-Net: Convolutional net- works for biomedical image segmentation,

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.304795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.592030Z digest=sha256:1483a2e0b5501ad87a887b9e0290358fe082cb12868503fd38c163614f0398c2

Observation 32d24dce-f953-4e4b-9999-38be749f82b2 · outbound

This paper cites Mapping large-scale mangroves along the Maritime Silk Road from 1990 to 2015 using a novel deep learning model and Landsat data,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Mapping large-scale mangroves along the Maritime Silk Road from 1990 to 2015 using a novel deep learning model and Landsat data,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.287185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.597359Z digest=sha256:c827987d0e9f7b315333bb446ff82cb87b19d5a9b4930ac0be586fc02fbf5d4f

Observation 9e0464bf-c1d6-4404-af7e-9ad0c58ea88e · outbound

This paper cites Capsules for Object Segmentation.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Capsules for Object Segmentation

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-10T21:57:18.602493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:57:18.602493Z digest=sha256:646e5df29b9bd228301848d6d7b16df993c9db01a3365bf04a5347629d3a0cb3

Observation 53ec686a-b406-41a4-a8cd-0cda128510e8 · outbound

This paper cites ME-Net: A deep convolutional neural network for extracting mangrove using Sentinel- 2A data,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping ME-Net: A deep convolutional neural network for extracting mangrove using Sentinel- 2A data,

Reference 42

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.270031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.610027Z digest=sha256:89c7ba335970e46044b9cf0d46218e1e526f26a7fedbc608a8b6120d2c95b5ad

Observation e09ed13f-826a-4d58-93c7-9063ad021a55 · outbound

This paper cites ADMM-ADAM: A new inverse imaging framework blending the advantages of convex optimization and deep learning,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping ADMM-ADAM: A new inverse imaging framework blending the advantages of convex optimization and deep learning,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.252333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.615193Z digest=sha256:cdb22a79dfffcc43b24cdd0a14239b99d67eb006402f343e3b91aaa91f48333c

Observation 27f9b1b9-39d6-4ff9-98b1-51102c1a970e · outbound

This paper cites Quantum- enhanced deep learning-based lithology interpretation from well logs,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Quantum- enhanced deep learning-based lithology interpretation from well logs,

Reference 44

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.231918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.620142Z digest=sha256:e58bdb08f47fc3b9f4860360a30217c79697751aa32b9363a6ff156ba701c720

Observation 872f8459-ca18-48eb-93c6-fbe83311bf0d · outbound

This paper cites Learning two-branch neural networks for image-text matching tasks,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Learning two-branch neural networks for image-text matching tasks,

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.212846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.625917Z digest=sha256:c4b89a0cefca21d1fc87f05ceae136b58a078dc1676a65642de728bed41c99a2

Observation 8dadc4bd-3e7f-4d06-9842-9319a161d7a1 · outbound

This paper cites Rectifier nonlinearities improve neural network acoustic models,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Rectifier nonlinearities improve neural network acoustic models,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.195094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.633904Z digest=sha256:d1952fb6c983dfade9ea3a8d03251aa0dadcce2f96ab69e200b02ea195a775c6

Observation 4e16164f-a659-41f1-a519-99e2dc4c09c6 · outbound

This paper cites an unresolved cited work.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-10T21:57:19.176923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.639792Z digest=sha256:ee38ab2d7593431112f1e2f00836df7b6e34a4c1f60d20733038606d0c65cd2f

Observation d69f77a8-d3c0-4227-94a0-39e128969669 · outbound

This paper cites PRIME: Blind Multispectral Unmixing Using Virtual Quantum Prism and Convex Geometry.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping PRIME: Blind Multispectral Unmixing Using Virtual Quantum Prism and Convex Geometry

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-08-10T21:57:18.808131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.646260Z digest=sha256:35ee40f4d739e44db16e821694f256555a63df33e43a9bef338ac7f9a0030daf

Observation 7b247d60-6a40-4f36-b507-e43a48e1792a · outbound

This paper cites Residual spectral– spatial attention network for hyperspectral image classification,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Residual spectral– spatial attention network for hyperspectral image classification,

Reference 49

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.155707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.653157Z digest=sha256:1ba63ea268d0883def9b790b2b58000ab92baa7f817c65c16ef73fb83d759a2b

Observation 07a642f4-59e3-4f18-9e09-236395065bcc · outbound

This paper cites Super-resolution map- ping based on spatial–spectral correlation for spectral imagery,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Super-resolution map- ping based on spatial–spectral correlation for spectral imagery,

Reference 50

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.135805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.660095Z digest=sha256:6402f485f54c14228aed1b9daaaa89e57653c1cce070146b49b7de4dcfd903f4

Observation b3cfb068-879a-46ff-b8da-f6ce790fde2d · outbound

This paper cites Robust dual graph self- representation for unsupervised hyperspectral band selection,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Robust dual graph self- representation for unsupervised hyperspectral band selection,

Reference 51

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.116663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.666722Z digest=sha256:78813f240c8fbf6eb2e0c1804ed747d658e17dcb597c4ba5dcbb11e800e98cb5

Observation 3a25632f-87f6-47f7-a09e-0ede4f50192b · outbound

This paper cites Hyperspectral image classification with deep feature fusion network,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Hyperspectral image classification with deep feature fusion network,

Reference 52

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.096735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.672657Z digest=sha256:2623e934d089857906d5c41ba6b2a78602c80301d1ea76d2810fd300586400c3

Observation c2f7f308-26e1-4dab-a55f-3498c06a83e7 · outbound

This paper cites Quantum copying: Beyond the no-cloning theorem,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Quantum copying: Beyond the no-cloning theorem,

Reference 53

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.080159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.679647Z digest=sha256:f2be767681ef8f9a87dcd3977cd72c3c1b3695d02e527648824569b45bccd28e

Observation 7bc127b7-fe16-484f-8105-464fc9f5e3c9 · outbound

This paper cites Sentinel-2 MSI: MultiSpectral Instrument, Level-2A,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Sentinel-2 MSI: MultiSpectral Instrument, Level-2A,

Reference 54

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raw_fallback, observed 2026-08-10T21:57:19.062925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.685976Z digest=sha256:46841e46dd81f4f8f7d6cf1276393374c2eefd7afcf15480c0b73058e766f09c

Observation c89886fd-f48b-4372-90c4-d17f3b28af17 · outbound

This paper cites An explicit and scene-adapted definition of convex self-similarity prior with application to unsupervised Sentinel-2 super-resolution,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping An explicit and scene-adapted definition of convex self-similarity prior with application to unsupervised Sentinel-2 super-resolution,

Reference 55

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raw_fallback, observed 2026-08-10T21:57:19.028473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.698471Z digest=sha256:7167d41efadc05f4fa9db1b8c19015ca98be9e4221c46f8d0666ce9372bac58a

Observation 989e987b-0366-4faf-ae26-5ba1239c014d · outbound

This paper cites A noval super-resolution model for 10-m mangrove mapping with landsat-5,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping A noval super-resolution model for 10-m mangrove mapping with landsat-5,

Reference 56

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raw_fallback, observed 2026-08-10T21:57:19.008369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.703772Z digest=sha256:cc017133b81c6fd7c82b6405baebb297ea2c41687ec4c6f782c361423c28dbcc

Observation 783e4523-b1d1-4590-be6b-cf05a9e8d35f · outbound

This paper cites Ash- former: Axial and sliding window-based attention with high-resolution transformer for automatic stratigraphic correlation,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Ash- former: Axial and sliding window-based attention with high-resolution transformer for automatic stratigraphic correlation,

Reference 57

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:18.990835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.709061Z digest=sha256:e9d9826b3248f397f279b0dbcabd69d7fd43e1d6fc0d6d81452e547b494471a4

Observation 975a44d2-4c0a-4ab2-88b6-b6fc2d0d9dd7 · outbound

This paper cites Seismic at- tributes aided horizon interpretation using an ensemble dense inception 13 transformer network,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Seismic at- tributes aided horizon interpretation using an ensemble dense inception 13 transformer network,

Reference 58

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raw_fallback, observed 2026-08-10T21:57:18.973028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.714474Z digest=sha256:e16a59f5ec3607a281b5db6dfcf7f54cd72a7024594a2dcc68c0bfae915e03b2

Observation 7c43e1a6-cdf9-4133-b48f-6471e8108a3f · outbound

This paper cites Clark Lab: Coastal Habitat Mapping: Mangrove and Pond Aqua- culture Conversion ,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Clark Lab: Coastal Habitat Mapping: Mangrove and Pond Aqua- culture Conversion ,

Reference 59

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:18.955528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.719862Z digest=sha256:0f3f8d1076e9744f654b3be29f002c335dd2746ea8ae324cae2dfba110b9b637

Observation ab294312-1a20-4100-8815-bce984aef544 · outbound

This paper cites Decoupled weight decay regularization,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Decoupled weight decay regularization,

Reference 60

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:18.937341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.726382Z digest=sha256:826034dc7abb7a0372a161ca3001f6cf6d3549b36086dbbb5db347735c7a3e35

Observation 0490cbce-55e1-4a0f-b182-74978bf17eae · outbound

This paper cites Detection of mangrove distribution in Pongok Island,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Detection of mangrove distribution in Pongok Island,

Reference 61

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:18.919000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.731321Z digest=sha256:15f8cfb1f8f498db8e1233f0113adba0f17f6be0eb248c4fd4d61e71eb8da3f0

Observation 85c63dab-7e6c-4e74-bcdf-612931b3095f · outbound

This paper cites Rates and drivers of mangrove de- forestation in Southeast Asia, 2000–2012,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Rates and drivers of mangrove de- forestation in Southeast Asia, 2000–2012,

Reference 62

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:18.902403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.736487Z digest=sha256:5783694324bbe79935b3faac644434d2c5f744bda08b7331292ad73e30ca2819

Observation e7e00075-2a4c-4757-b6bf-36076037fad9 · outbound

This paper cites Accuracy and inaccuracy assessments in land- cover classification,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Accuracy and inaccuracy assessments in land- cover classification,

Reference 63

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:18.885094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.743167Z digest=sha256:4ae7e5936d7012c9f6cdf952d2fc15b896798d0a49bdbdccc5631c7d389b55b4

Observation 3db2ee0a-17e9-46b3-932a-94a3de4f360f · outbound

This paper cites Comparative assessment of the measures of thematic classification accuracy,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Comparative assessment of the measures of thematic classification accuracy,

Reference 64

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:18.867724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.749866Z digest=sha256:f0661aa68feb1e14ffd80cd325488bb29ae34f0aaa90dd2e442fd0c500a69172

Observation a8908557-3ae9-4f1c-8ea7-5c65bef7cb62 · outbound

This paper cites Coefficient kappa: Some uses, misuses, and alternatives,.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Coefficient kappa: Some uses, misuses, and alternatives,

Reference 65

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verified fuzzy
raw_fallback, observed 2026-08-10T21:57:18.850448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.754849Z digest=sha256:77e99eeca600769a360a7894d433d93cddd4848162b5873bf03f97aabd342aee

Observation dfe0ea81-3c02-47be-b9ad-1de33dee4796 · outbound

This paper cites Available: https://developers.google.com/earth-engine/ datasets/catalog/COPERNICUS S2 SR#bands.

Quantum Feature-Empowered Deep Classification for Fast Mangrove Mapping Available: https://developers.google.com/earth-engine/ datasets/catalog/COPERNICUS S2 SR#bands

Reference 2022

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:57:19.045938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T21:57:18.692375Z digest=sha256:f9823b9d580ea6f3b3534ff7f3e3f73ae73e6db6e7fae14b1c28971cf0d84594

Pith citing papers

No inbound Pith citation observations are available.