Paper Citation Record · LEDGER

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception

As of 7 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2505.18303.

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

pith.paper-citation-record.v1
2505.18303 v1

Coverage vector

measured 43 of 43 reference resolution

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measured 44 of 44 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:39:13.483190Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T11:39:13.816884Z

Reference resolution

43 of 43 outbound references displayed

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External citation measurements

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Outbound references

Observation fc463b55-0954-4841-b14e-5a78936800ca · outbound

This paper cites A revolution in optical manipulation,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception A revolution in optical manipulation,

Reference 1

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Observation acadaf6c-7aa4-43ba-aa45-0534395206cf · outbound

This paper cites Automated manipulation of biological cells using gripper formations controlled by optical tweezers,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Automated manipulation of biological cells using gripper formations controlled by optical tweezers,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:26.706478Z

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Observation f28f1c50-f43d-436e-ad45-e2fca4222a05 · outbound

This paper cites Fabrication and optical manipulation of micro-robots for biomedical applications,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Fabrication and optical manipulation of micro-robots for biomedical applications,

Reference 3

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Observation e0ab557e-91ca-4474-a9f2-c42715abfb74 · outbound

This paper cites Optical tweezers: Phototoxicity and thermal stress in cells and biomolecules,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Optical tweezers: Phototoxicity and thermal stress in cells and biomolecules,

Reference 4

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Observation 3ee17fae-d62a-4b8e-b09a-c99792b6e4dd · outbound

This paper cites Opto-refrigerative tweezers,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Opto-refrigerative tweezers,

Reference 5

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Observation ac97dcb8-5784-4eae-8129-4b7a1a70ef19 · outbound

This paper cites Distributed force control for microrobot manipulation via planar multi-spot optical tweezer,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Distributed force control for microrobot manipulation via planar multi-spot optical tweezer,

Reference 6

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Observation 27e7f321-4dd0-496f-b6e1-13b6070e4b56 · outbound

This paper cites Reconfigurable magnetic microrobot swarm: Multimode trans- formation, locomotion, and manipulation,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Reconfigurable magnetic microrobot swarm: Multimode trans- formation, locomotion, and manipulation,

Reference 7

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Observation 5593e854-bf73-4c56-9aff-b85a37630ea3 · outbound

This paper cites Measurement of van der waals force using oscillating optical tweezers,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Measurement of van der waals force using oscillating optical tweezers,

Reference 8

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Observation 0ad67aca-6338-4aa6-b674-954618025465 · outbound

This paper cites Micro-object pose estimation with sim-to-real transfer learning using small dataset,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Micro-object pose estimation with sim-to-real transfer learning using small dataset,

Reference 9

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This paper cites A review on micro- scopic visual servoing for micromanipulation systems: Applications in micromanufacturing, biological injection, and nanosensor assembly,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception A review on micro- scopic visual servoing for micromanipulation systems: Applications in micromanufacturing, biological injection, and nanosensor assembly,

Reference 10

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Observation fe503ec3-02a5-4372-a1b9-19beff797817 · outbound

This paper cites Reinforce- ment learning with artificial microswimmers,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Reinforce- ment learning with artificial microswimmers,

Reference 11

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Observation 0f195be8-33d3-42cc-b8b6-02c1f299c5ab · outbound

This paper cites Deep learning for visual localization and mapping: A survey,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Deep learning for visual localization and mapping: A survey,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:26.357081Z

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Observation 7ec53958-f611-40df-83ce-4d3fae16e2ad · outbound

This paper cites Three-dimensional optical microrobot orientation estimation and tracking using deep learning,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Three-dimensional optical microrobot orientation estimation and tracking using deep learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:26.331086Z

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Observation 69ea78f7-37ac-4dc8-8eda-7dd3f20892f3 · outbound

This paper cites Control of self-winding microrobot using an electromagnetic drive system: integration of movable electromagnetic coil and permanent magnet,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Control of self-winding microrobot using an electromagnetic drive system: integration of movable electromagnetic coil and permanent magnet,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:26.301660Z

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Observation 081165df-b001-4999-83bf-780ae099bf67 · outbound

This paper cites Machine learning for micro-and nanorobots,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Machine learning for micro-and nanorobots,

Reference 15

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Observation 1dbaffa4-c4a7-42ed-af26-d954928e3ae4 · outbound

This paper cites Self-supervised learning methods and applications in medical imaging analysis: A survey,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Self-supervised learning methods and applications in medical imaging analysis: A survey,

Reference 16

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Observation a4e530e6-9c90-4622-9513-26cccbe62dc7 · outbound

This paper cites The joint evaluated fission and fusion nuclear data library, jeff-3.3,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception The joint evaluated fission and fusion nuclear data library, jeff-3.3,

Reference 17

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Observation f24ba0b1-9282-4b2b-a180-07c80e4eae8c · outbound

This paper cites Invited review article: review of post-process optical form metrology for industrial-grade metal additive manufactured parts,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Invited review article: review of post-process optical form metrology for industrial-grade metal additive manufactured parts,

Reference 18

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Observation beef2ff7-c8ec-47e4-aa59-f373743227af · outbound

This paper cites Different thresholding tech- niques in image processing: A review,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Different thresholding tech- niques in image processing: A review,

Reference 19

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Observation d2dc55ad-3ff1-4266-aff1-0d2525f4f51b · outbound

This paper cites Image seg- mentation using morphological operations,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Image seg- mentation using morphological operations,

Reference 20

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A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Kanatani, Y

Reference 21

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Observation a541cc5a-028d-4dbd-b877-a3e3f49713f1 · outbound

This paper cites Optical microsphere nano-imaging: progress and challenges,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Optical microsphere nano-imaging: progress and challenges,

Reference 22

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Observation 9ffc38bd-7493-4cad-9f18-fcd6ec39e864 · outbound

This paper cites Advancements in machine learning for microrobotics in biomedicine,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Advancements in machine learning for microrobotics in biomedicine,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:35:25.977719Z

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Observation e6bab7fd-f038-41c8-aa69-6cfad12c524f · outbound

This paper cites An accurate perception method for low contrast bright field microscopy in heterogeneous microenvironments,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception An accurate perception method for low contrast bright field microscopy in heterogeneous microenvironments,

Reference 24

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Observation 55ac6fa3-2192-4c90-a16e-28ccbfe1bdcd · outbound

This paper cites Three-dimensional pose estimation of optically transparent microrobots,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Three-dimensional pose estimation of optically transparent microrobots,

Reference 25

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Observation 5c37c70c-6f3b-461b-9749-39e4da765181 · outbound

This paper cites Data-driven microscopic pose and depth estimation for optical microrobot manipulation,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Data-driven microscopic pose and depth estimation for optical microrobot manipulation,

Reference 26

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Observation 6862159e-2d1a-49ca-88a4-a69d757075e5 · outbound

This paper cites Finer features for functional microdevices,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Finer features for functional microdevices,

Reference 27

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Observation 59fd443c-0b85-4a70-a8d5-b1185e819675 · outbound

This paper cites Sculpting the object,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Sculpting the object,

Reference 28

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Observation df47e56c-4dce-4452-91dd-1f837364010f · outbound

This paper cites Numerical modelling of optical trapping,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Numerical modelling of optical trapping,

Reference 29

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Observation 1e06f5e2-d71c-45f7-b9d4-857f78820861 · outbound

This paper cites Two-dimensional signal and image processing,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Two-dimensional signal and image processing,

Reference 30

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This paper cites A computational approach to edge detection,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception A computational approach to edge detection,

Reference 31

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

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 32

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A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Deep residual learning for image recognition,

Reference 33

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Observation 90d5df02-c6f9-4e84-bb1e-0e85e896858c · outbound

This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 34

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This paper cites MobileNetV2: Inverted Residuals and Linear Bottlenecks.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception MobileNetV2: Inverted Residuals and Linear Bottlenecks

Reference 35

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Observation c6d0bcc1-b8d4-4cc3-9e3e-ec1fc74431ee · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 36

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This paper cites Optuna: A next-generation hyperparameter optimization framework,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Optuna: A next-generation hyperparameter optimization framework,

Reference 37

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This paper cites Torchvision: Pytorch’s computer vision library.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Torchvision: Pytorch’s computer vision library

Reference 38

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A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Imagenet: A large-scale hierarchical image database,

Reference 39

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This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Grad-cam: Visual explanations from deep networks via gradient-based localization,

Reference 40

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This paper cites Digital twin modeling,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Digital twin modeling,

Reference 41

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This paper cites Generative adversarial net- works,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Generative adversarial net- works,

Reference 42

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This paper cites Diffusion models in vision: A survey,.

A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception Diffusion models in vision: A survey,

Reference 43

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Pith citing papers

Observation 0dca3f42-1fb1-4968-9f82-0df12b617a5f · inbound

Physics-Informed Machine Learning with Adaptive Grids for Optical Microrobot Depth Estimation cites this paper.

Physics-Informed Machine Learning with Adaptive Grids for Optical Microrobot Depth Estimation A Dataset and Benchmarks for Deep Learning-Based Optical Microrobot Pose and Depth Perception

Reference 29

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