Paper Citation Record · LEDGER

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks

As of 23 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2412.00302.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.00302 v2

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:35:40.925921Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

14 of 14 outbound references displayed

verified exact0
verified fuzzy12
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0d440eb9-6131-4593-bef0-639bfec51ceb · outbound

This paper cites A joint convolutional cross vit network for hyperspectral and light detection and ranging fusion classification,.

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks A joint convolutional cross vit network for hyperspectral and light detection and ranging fusion classification,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:35:41.165731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 099fdfd3-e203-4028-8902-94291312b523 · outbound

This paper cites A survey on deep learning for multimodal data fusion,.

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks A survey on deep learning for multimodal data fusion,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:35:41.150413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ea163c2d-c5ab-4533-934c-836b9dce8e60 · outbound

This paper cites An adaptive multi-sensor data fusion method based on deep convolutional neural networks for fault diagnosis of planetary gearbox,.

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks An adaptive multi-sensor data fusion method based on deep convolutional neural networks for fault diagnosis of planetary gearbox,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:35:41.135515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation caf66ece-dd12-47d5-9446-fcbc281cf9a1 · outbound

This paper cites Lidar- guided cross-attention fusion for hyperspectral band selection and image classification,.

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks Lidar- guided cross-attention fusion for hyperspectral band selection and image classification,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:35:41.119681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fc0a385c-f4b1-4b87-8b1c-e43c269fd59f · outbound

This paper cites Deep encoder– decoder networks for classification of hyperspectral and lidar data,.

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks Deep encoder– decoder networks for classification of hyperspectral and lidar data,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:35:41.102555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 40bb31d6-ad28-4fd1-ad3c-5c7797fe7267 · outbound

This paper cites Collaborative contrastive learning for hyperspectral and lidar classification,.

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks Collaborative contrastive learning for hyperspectral and lidar classification,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:35:41.086544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 95399eb5-4f39-4379-a39d-f8ecdc672127 · outbound

This paper cites Multisource remote sensing data classification based on convolutional neural network,.

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks Multisource remote sensing data classification based on convolutional neural network,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:35:41.070733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 77e64f44-d6a9-499a-a5c5-92deee6b9c4f · outbound

This paper cites Deep fusion of hyperspectral and lidar images using attention-based cnn,.

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks Deep fusion of hyperspectral and lidar images using attention-based cnn,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:35:41.055228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 94950a34-92f4-43d7-8709-8a947542134b · outbound

This paper cites Vision transformers: From semantic segmentation to dense prediction,.

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks Vision transformers: From semantic segmentation to dense prediction,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:35:41.039129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3fa779f2-f880-44d7-953e-504698382bff · outbound

This paper cites Spectralformer: Rethinking hyperspectral image classification with transformers,.

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks Spectralformer: Rethinking hyperspectral image classification with transformers,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T05:35:40.906018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c461af0-5caa-49f3-b082-d00f934e3852 · outbound

This paper cites Hsi-bert: Hyperspectral image classification using the bidirectional encoder representation from transformers,.

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks Hsi-bert: Hyperspectral image classification using the bidirectional encoder representation from transformers,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:35:41.013085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 578e36b9-19c8-46cc-8679-ed5703fce668 · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks Efficiently Modeling Long Sequences with Structured State Spaces

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T05:35:40.916037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8352e6ea-db40-46b8-9ed2-561515b7c61a · outbound

This paper cites More diverse means better: Multimodal deep learning meets remote- sensing imagery classification,.

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks More diverse means better: Multimodal deep learning meets remote- sensing imagery classification,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:35:40.996644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9aca1d1a-e2a7-4abb-bf95-ce7bfbc433af · outbound

This paper cites S 2enet: Spatial–spectral cross-modal en- hancement network for classification of hyperspectral and lidar data,.

HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Non-Linear Feature Learning Networks S 2enet: Spatial–spectral cross-modal en- hancement network for classification of hyperspectral and lidar data,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:35:40.980615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.