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Paper Citation Record · LEDGER

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications

As of 7 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2508.00900.

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

pith.paper-citation-record.v1
2508.00900 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T13:10:19.639067Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

59 of 59 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 541f4ea0-00f7-4d43-9090-19aaffe60d57 · outbound

This paper cites Field with the fragrant damask rose,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Field with the fragrant damask rose,

Reference 1

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verified fuzzy
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Observation 2eba026e-9430-42de-a245-4b80d2107f9e · outbound

This paper cites YOLOv4: Optimal Speed and Accuracy of Object Detection.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 2

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Source-reported events for the cited work

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Observation 21b6512e-2e42-41aa-9567-cbfa67ee93d3 · outbound

This paper cites Voxelnet: End-to-end learning for point cloud based 3d object detection,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Voxelnet: End-to-end learning for point cloud based 3d object detection,

Reference 3

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Observation 1f4c4971-2fff-4bed-999e-14d008ca2a26 · outbound

This paper cites Center- net: Keypoint triplets for object detection,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Center- net: Keypoint triplets for object detection,

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 46c77bb3-1a8c-4e48-a723-ed5b006887d4 · outbound

This paper cites Objects as Points.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Objects as Points

Reference 5

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Source-reported events for the cited work

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Observation cfa74f18-7c3a-4f7f-9c80-27fefe1851e7 · outbound

This paper cites Frustum pointnets for 3d object detection from rgb-d data,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Frustum pointnets for 3d object detection from rgb-d data,

Reference 6

Resolution
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 8945747a-360d-4ed3-99d8-d78c5193d7dd · outbound

This paper cites Voting for voting in online point cloud ob- ject detection.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Voting for voting in online point cloud ob- ject detection

Reference 7

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation a14d8d65-9c53-41af-979b-f96650724ecc · outbound

This paper cites 3d object proposals using stereo imagery for accurate object class detec- tion,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications 3d object proposals using stereo imagery for accurate object class detec- tion,

Reference 8

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 3300d0fd-eda6-45f1-be08-b10357ba7763 · outbound

This paper cites Efficient joint segmen- tation, occlusion labeling, stereo and flow estimation,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Efficient joint segmen- tation, occlusion labeling, stereo and flow estimation,

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4d92aa90-1a70-4d00-93bb-b41505c2a2fd · outbound

This paper cites Stereo r-cnn based 3d object detection for autonomous driving,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Stereo r-cnn based 3d object detection for autonomous driving,

Reference 10

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 32558e48-59d9-4e3f-92c1-01f57b400c79 · outbound

This paper cites Faster r-cnn: Towards real- time object detection with region proposal networks,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Faster r-cnn: Towards real- time object detection with region proposal networks,

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 647586d2-61c3-4d9c-b52f-5de587a0eb54 · outbound

This paper cites Monocular 3d object detection for autonomous driving,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Monocular 3d object detection for autonomous driving,

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation a692b3b0-1241-469a-8888-ff9b1d547d2e · outbound

This paper cites Monogrnet: A geometric reasoning net- work for monocular 3d object localization,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Monogrnet: A geometric reasoning net- work for monocular 3d object localization,

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 7e4a7c70-91f3-4fbd-b78b-aec98a5dad58 · outbound

This paper cites Unsupervised cnn for single view depth estimation: Geometry to the rescue,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Unsupervised cnn for single view depth estimation: Geometry to the rescue,

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 564a8c0b-f01c-4f5d-976d-242dd51f67a6 · outbound

This paper cites Unsupervised monoc- ular depth estimation with left-right consistency,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Unsupervised monoc- ular depth estimation with left-right consistency,

Reference 15

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation f01af081-0b05-48b3-a68f-f04c19f49b79 · outbound

This paper cites Using channel pruning-based yolo v4 deep learning algorithm for the real-time and accurate detection of apple flowers in natural environments,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Using channel pruning-based yolo v4 deep learning algorithm for the real-time and accurate detection of apple flowers in natural environments,

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 07c221e1-afdd-4d2d-bd14-ef0abc27987e · outbound

This paper cites Real-time apple detection system using embedded systems with hardware accelerators: An edge ai application,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Real-time apple detection system using embedded systems with hardware accelerators: An edge ai application,

Reference 17

Resolution
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Source-reported events for the cited work

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Observation 12b0df2a-7730-4ea4-847a-205dfe9b9229 · outbound

This paper cites Deep learning-based apple detection using a suppression mask r-cnn,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Deep learning-based apple detection using a suppression mask r-cnn,

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e3c071e0-f0e0-4d5f-bef9-063e2418df16 · outbound

This paper cites Mask r-cnn,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Mask r-cnn,

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 36f9029f-01d3-4f57-8269-e4709dca5d42 · outbound

This paper cites Flower classifica- tion using deep convolutional neural networks,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Flower classifica- tion using deep convolutional neural networks,

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 3e5ab536-bcff-458b-9737-7fe8bbf7aead · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 21

Resolution
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Source-reported events for the cited work

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Observation b2047ae3-c20a-4ab3-8556-e934020ca79c · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Imagenet: A large-scale hierarchical image database,

Reference 22

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 582f0d3a-77c9-42d7-9790-3d3321ed909c · outbound

This paper cites A visual vocabulary for flower classi- fication,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications A visual vocabulary for flower classi- fication,

Reference 23

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation fa45facd-ad37-4994-b87c-48380aa3ff85 · outbound

This paper cites Evaluation of model-based interactive flower recognition,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Evaluation of model-based interactive flower recognition,

Reference 24

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation a25c6791-4093-4963-9bb1-9a4071dbda46 · outbound

This paper cites Fruit detection, segmentation and 3d visuali- sation of environments in apple orchards,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Fruit detection, segmentation and 3d visuali- sation of environments in apple orchards,

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 84a8ba1c-f995-4466-8e4a-e7a09b880d40 · outbound

This paper cites Flower detection using advanced deep learning techniques,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Flower detection using advanced deep learning techniques,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.956996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation d2d06883-b892-4f2f-9e60-a46ba35e601c · outbound

This paper cites Apple, peach, and pear flower de- tection using semantic segmentation network and shape constraint level set,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Apple, peach, and pear flower de- tection using semantic segmentation network and shape constraint level set,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.948908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4d992ae2-26e6-47a2-8240-5ddd6231a820 · outbound

This paper cites Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,

Reference 28

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:10:19.551166Z digest=sha256:190a990adaaa3ed3f95beb18ff4eeae376803f6083dd67e50f57f235f72e7b6d

Observation 15613941-7234-4aae-8ccf-64ff32171ac9 · outbound

This paper cites Coco-stuff: Thing and stuff classes in context,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Coco-stuff: Thing and stuff classes in context,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.934758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 829efb6f-a9a5-4b21-a586-e59b6b793fc8 · outbound

This paper cites Real-time detection of kiwifruit flower and bud simultane- ously in orchard using yolov4 for robotic pollination,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Real-time detection of kiwifruit flower and bud simultane- ously in orchard using yolov4 for robotic pollination,

Reference 30

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 6cb350e4-5111-49e0-91c2-96ceaadae07d · outbound

This paper cites Image based mango fruit detection, localisation and yield estimation using multiple view geome- try,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Image based mango fruit detection, localisation and yield estimation using multiple view geome- try,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.917305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.558364Z digest=sha256:0d01c4d1821400f36603cf315119a551d646048bdb6b0c7e80eccbca4b36e351

Observation dc37d67e-4f20-49b2-a92b-b40aec1d8335 · outbound

This paper cites An automated fruit harvesting robot by using deep learn- ing,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications An automated fruit harvesting robot by using deep learn- ing,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.908896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.561409Z digest=sha256:f65f219d09df68bf8bc598a2590d6f437dfa89d8b9565c00f2f3f41f50cc5f78

Observation 64452f92-7f5e-456b-a917-20c6899d3f39 · outbound

This paper cites Ssd: Single shot multibox detector,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Ssd: Single shot multibox detector,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.900876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.564526Z digest=sha256:133f4bb14b7bf89bed5981723c4a87547bb801be81ac336ab74b567acddb74aa

Observation b0b3f3b3-fcb0-45b7-ac1b-4b7113565d62 · outbound

This paper cites Robotic harvesting of rosa damascena using stereoscopic ma- chine vision,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Robotic harvesting of rosa damascena using stereoscopic ma- chine vision,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.892914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.567529Z digest=sha256:93dffabb59ca2721b91eaaca7664dc39f66ea531a09ed0baadadb85c7487c8cd

Observation 2047260f-0a9f-4836-aafe-480a534f3201 · outbound

This paper cites Geometry-aware fruit grasping estimation for robotic har- vesting in apple orchards,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Geometry-aware fruit grasping estimation for robotic har- vesting in apple orchards,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.883892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.570181Z digest=sha256:e014759b7d286fa4730eb5e61a3aa4d8a5fe86a734c64b962f1dbfc910956219

Observation c9e519df-a548-40b5-bcf6-003e62b3bcc5 · outbound

This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Pointnet: Deep learning on point sets for 3d classification and segmentation,

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T13:10:19.573119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:10:19.573119Z digest=sha256:3cd5a52f72250db670adda2bbe8d0f70d156914fb6d5fed70bfedaa9fda83d75

Observation fb432f10-36db-4ff5-8bbc-3d8e86f69a3a · outbound

This paper cites Octomap: An efficient probabilistic 3d mapping framework based on octrees,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Octomap: An efficient probabilistic 3d mapping framework based on octrees,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.870948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.576105Z digest=sha256:03b2406006572861d2e2ad32a3dbda4ba3328e382ca2a3db686046109b2c763c

Observation 28af7ca7-6294-404b-a985-bffb533ab55f · outbound

This paper cites Rapid strawberry ripeness detection and 3d localization of picking point based on improved yolo v8-pose with rgb-camera,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Rapid strawberry ripeness detection and 3d localization of picking point based on improved yolo v8-pose with rgb-camera,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.862565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.578642Z digest=sha256:f0272c03c32ee0c02670dc4cdbecc56af9d4011b876ea0093486bb8d8348eb5e

Observation dd278f3d-6270-4176-9a75-9b866cd08165 · outbound

This paper cites Ultralytics YOLO,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Ultralytics YOLO,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T13:10:19.581006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:10:19.581006Z digest=sha256:4d1f15e169b78ef7d1b5e3c00e06bd18ee29908844631ff4b064341338292089

Observation 376faac2-ecf4-4ae2-a50d-b3eaff63be24 · outbound

This paper cites Efficientdet: Scalable and efficient object detection,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Efficientdet: Scalable and efficient object detection,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.849502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.583804Z digest=sha256:ed6c676a884be2f461789c792c6a0dfc3ee2f47e5ddfe415fe424714c689af35

Observation e23693a0-b095-40a5-96cb-67e4ec258d19 · outbound

This paper cites MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications MobileViTv3: Mobile-Friendly Vision Transformer with Simple and Effective Fusion of Local, Global and Input Features

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T13:10:19.586800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:10:19.586800Z digest=sha256:cf359a156301202b284053d387b197e2fe3f4adf4561e723b113cd0b6ebbf306

Observation f48d8970-5af3-499d-aa1a-0452694aa4dd · outbound

This paper cites Tomato pose estimation us- ing the association of tomato body and sepal,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Tomato pose estimation us- ing the association of tomato body and sepal,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.842011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.589843Z digest=sha256:67540fe36dfadd227b5a6967ff87150d9a7083a67385cf29ef449224c2de73bb

Observation a362661f-95ae-4dfa-bb2b-d97b48d9c1fb · outbound

This paper cites Organization.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Organization

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.833936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.592910Z digest=sha256:96d04071927fea6d6395ddbc955b996453b87466b16c5991852a802650928a6a

Observation eec2e460-6631-4c55-a704-e14c7bb510e3 · outbound

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

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications U-net: Convolutional net- works for biomedical image segmentation,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.826234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.596092Z digest=sha256:82a5583372e9db46e04b2213aaa87eaa829e6df6d6a48a97a77aed3268b3f88b

Observation 52e7873e-227d-4837-a1a5-39303a95c972 · outbound

This paper cites an unresolved cited work.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Unresolved cited work

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T13:10:19.599213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:10:19.599213Z digest=sha256:8b47f849483db65ebb9a0d108b5cc3343b2e182cfe87ccaede21a4e35f3b7fa9

Observation c665ffb1-b629-41b7-a290-3833510ba6be · outbound

This paper cites Efficientnetv2: Smaller models and faster training,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Efficientnetv2: Smaller models and faster training,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.812518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.602016Z digest=sha256:886fbad749f2852986c9f8346694c3725e07b73537b722397a5ba2ba31f6dd05

Observation 06fe87b8-599c-4cf1-9f62-3c94e999723b · outbound

This paper cites Going deeper with convolu- tions,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Going deeper with convolu- tions,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.804755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.604688Z digest=sha256:da4aa390a2b50a876b67dc16490e79e4add12abd3cf86b11373d41dbe5d94507

Observation 14f133c3-1244-4a81-943f-07144a667fbe · outbound

This paper cites Cross-entropy loss functions: The- oretical analysis and applications,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Cross-entropy loss functions: The- oretical analysis and applications,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.796888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.608185Z digest=sha256:ecc406cec8da717882ef94137c9f6ad43148c36fa500ab7101794be756f4aa15

Observation 180f339d-4c6c-4727-9fac-0f8bae5785c4 · outbound

This paper cites Fast r-cnn,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Fast r-cnn,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.788713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.611203Z digest=sha256:c420cd13cf094cd4ae99c522a07f863bef6a6200a297fb7f60a770ab26307ef4

Observation f726ec59-1cee-4057-ba29-b9983fd5a98d · outbound

This paper cites Template matching,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Template matching,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.780844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.613638Z digest=sha256:088e7fc57964ce69070591cdf69b916319cc041b872b9e7e777cf9bbb5db3195

Observation 7ad0932e-5c8e-48b9-b8dc-cedcf88264a6 · outbound

This paper cites Image rectification,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Image rectification,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.773536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.616210Z digest=sha256:e42878e0a2e83e43b6f16b1d53c88476dd6f52665bdabed379208e0462aa4378

Observation 20aa1a98-7f61-4f53-9c27-aeb63da895fa · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Are we ready for autonomous driving? the kitti vision benchmark suite,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.765114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.618997Z digest=sha256:6ff1aeb415ae094c60a071055da3604d6b8e94a155b1c3bd257392e585a71964

Observation a971b6c4-d83c-4fc9-a2d7-972c164537ad · outbound

This paper cites Location of apples in trees using stereo- scopic vision,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Location of apples in trees using stereo- scopic vision,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.755686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.621607Z digest=sha256:08e7304bdb019662aff085b096709686b416209e94b4947463de6b38f329ad68

Observation f0bad0a6-0d95-4caf-af25-8b57fcda5fd5 · outbound

This paper cites De- formable convolutional networks,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications De- formable convolutional networks,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.745998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.624769Z digest=sha256:15a9b709a21099c7d1b8f35c517ae935f016e07e0f9431f8368dee003d640062

Observation be60961e-4179-4bc7-9475-7fc4ce9b2b59 · outbound

This paper cites Siamese neural net- works for one-shot image recognition,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Siamese neural net- works for one-shot image recognition,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.737434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.627643Z digest=sha256:8f0d6a42981d7f00ececa838871ed8a567b7cb6238bab0f50bcd1da76ed1e7fd

Observation 595f6019-56c2-4648-8c75-e481b71ccbfe · outbound

This paper cites Widening siamese ar- chitectures for stereo matching,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Widening siamese ar- chitectures for stereo matching,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.728677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.630183Z digest=sha256:c5048d400991bb99782d046b2193e225d6bea508e62fd6a3bda69c599d65f240

Observation e43cb868-354e-4afe-b047-14583f414202 · outbound

This paper cites Dynamic feature fusion for visual object detection and segmen- tation,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Dynamic feature fusion for visual object detection and segmen- tation,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.718674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.632980Z digest=sha256:7a68abcc184864c9ac9dd0cc09ec3b9bfd5660cd65394ccf14553abcb047c800

Observation df5ec68e-4ceb-467f-b494-16d1d929fbd4 · outbound

This paper cites Self-Supervised Joint Learning Framework of Depth Estimation via Implicit Cues.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Self-Supervised Joint Learning Framework of Depth Estimation via Implicit Cues

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-06T13:10:19.635998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:10:19.635998Z digest=sha256:e2e4af2cef058b529e4da8acd66cf5588301c7dbbf2ecf9c1de67526f1f75c0d

Observation c748ea09-5364-4489-aa58-da898f069227 · outbound

This paper cites Transdssl: Trans- former based depth estimation via self-supervised learning,.

Sparse 3D Perception for Rose Harvesting Robots: A Two-Stage Approach Bridging Simulation and Real-World Applications Transdssl: Trans- former based depth estimation via self-supervised learning,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.709218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T13:10:19.639067Z digest=sha256:a712822c24570b20c599a8a8aac5a9872849ed916eee0c15b94af691931cd6ca

Pith citing papers

No inbound Pith citation observations are available.