Pith. sign in

Paper Citation Record · LEDGER

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation

As of 14 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2607.27058.

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

pith.paper-citation-record.v1
2607.27058 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-30T12:27:40.619018Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

33 of 33 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved33
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fbd19ee3-f665-4c67-b9da-aa2cf713af6e · outbound

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

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.481552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.481552Z digest=sha256:2a44e8a4d71a24bbdf6dcf497c13f316e56d4ca3c162d8bebe2571f749cf9302

Observation cb859272-30cf-4f59-a52f-a0c89b685726 · outbound

This paper cites You only look once: Unified, real-time object detection.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation You only look once: Unified, real-time object detection

Reference 2

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.484952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.484952Z digest=sha256:9c271e6b10e111e3d5df8f36f84b14e9cf139d469253716b124f9dea769b5a67

Observation 489731ec-727d-41ba-9e8b-59b3276316be · outbound

This paper cites Yolo9000: better, faster, stronger.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Yolo9000: better, faster, stronger

Reference 3

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.487941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.487941Z digest=sha256:96e1678d51ed8df8d8c43bcbd66ba933bfeaff33baf72040ab6fc05e28efa9ef

Observation 936ba9be-cf43-42be-a8fa-73a8aa68f745 · outbound

This paper cites YOLOv3: An Incremental Improvement.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation YOLOv3: An Incremental Improvement

Reference 4

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.490897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.490897Z digest=sha256:04a2e924360227909e02c97d02278701febd3a4b747508e0f3fb2a4e0effcba9

Observation dad0a04a-1e05-4d52-b183-3850ac8b6f55 · outbound

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

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.493898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.493898Z digest=sha256:02960b313345e92521d44119b71a3b0058a0044b1abc4e9b04f71a405cf86fef

Observation d3979da1-480f-4812-ba16-edd1ec27aa39 · outbound

This paper cites Yolov5 https://github.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Yolov5 https://github

Reference 6

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.497373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.497373Z digest=sha256:c9e0bce0c4d1f0f0668a12061884b628a901d761818aa75d57a48d2330bda22a

Observation b44aa081-edc2-4d3c-9b62-38f5c0110ff2 · outbound

This paper cites End-to-end object detection with transformers.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation End-to-end object detection with transformers

Reference 7

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.500404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.500404Z digest=sha256:7aba4f774ecf6041cccfdca2ad74b5d35eb9a8eac272133c24fbd402061aa50b

Observation 5e28a76e-b9d0-4501-b31e-383b6f063c0c · outbound

This paper cites Detrs beat yolos on real- time object detection.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Detrs beat yolos on real- time object detection

Reference 8

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.503445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.503445Z digest=sha256:a4f9f2700d0f3922f3b949a9259b2072e9132a7d64fc43299386dc5dd9b3ee4f

Observation b976e6ae-77e9-41ab-a890-0ff5cd73cc17 · outbound

This paper cites Evaluating yolo architectures: Implications for real-time vehicle detection in urban environments of bangladesh.arXiv preprint arXiv:2509.05652, 2025.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Evaluating yolo architectures: Implications for real-time vehicle detection in urban environments of bangladesh.arXiv preprint arXiv:2509.05652, 2025

Reference 9

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.506120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.506120Z digest=sha256:c90f89ac471d3ebd206e323f9818c1bbd7eca3709f7a1257e91855b98e5fdf06

Observation 15839f5e-bf98-4ba7-8691-b5d210382c4e · outbound

This paper cites Domain Generalization in Autonomous Driving: Evaluating YOLOv8s, RT-DETR, and YOLO-NAS with the ROAD-Almaty Dataset.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Domain Generalization in Autonomous Driving: Evaluating YOLOv8s, RT-DETR, and YOLO-NAS with the ROAD-Almaty Dataset

Reference 10

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.508985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.508985Z digest=sha256:2e7e96262cc8ef3f5516c5df11b8611f887dec0882cdc683ac7d62246991003a

Observation 6f162f5a-da20-43ef-bc7c-6e8089c4b272 · outbound

This paper cites First qualitative observations on deep learning vision model YOLO and DETR for automated driving in Austria.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation First qualitative observations on deep learning vision model YOLO and DETR for automated driving in Austria

Reference 11

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.511671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.511671Z digest=sha256:75aa55e93f76de51bd66fc5aa12e47870558bde9c8d22238a7fa02a92cf08664

Observation 514480d8-2313-4740-9d8e-2f6e765fd2ae · outbound

This paper cites Revisiting unreasonable effectiveness of data in deep learning era.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Revisiting unreasonable effectiveness of data in deep learning era

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.514363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.514363Z digest=sha256:0c467ca015858c1ff3372e08eb8b739fd890d3e6d19adc6292b99deb019bf652

Observation 876a20b0-2e09-4137-9d61-c836ee05bdc9 · outbound

This paper cites Vision meets robotics: The kitti dataset.The international journal of robotics research, 32(11):1231–1237, 2013.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Vision meets robotics: The kitti dataset.The international journal of robotics research, 32(11):1231–1237, 2013

Reference 13

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.517124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.517124Z digest=sha256:0b9e18d01b7bcd603b55a69860b6e1d25caeea6096fdfcd5ee3665d6141641b6

Observation 36a44a1f-8f9f-457f-ac97-e0461acb6e41 · outbound

This paper cites Bdd100k: A diverse driving dataset for heterogeneous multitask learning.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Bdd100k: A diverse driving dataset for heterogeneous multitask learning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.519691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.519691Z digest=sha256:aedbe1298803a765e2bbf4476002958ce6e8751eb8ad903105df9fd56348a960

Observation 9221e0d6-3124-49ac-bceb-9c4f0e3cdc79 · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation nuscenes: A multimodal dataset for autonomous driving

Reference 15

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.522224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.522224Z digest=sha256:91f7e79f2c9260d1730ba766af7ae67afdf62dd64dabdcbbcaf534cd8daf5910

Observation 97bfb156-950a-41be-873d-2ac5207363f6 · outbound

This paper cites Scalability in perception for autonomous driving: Waymo open dataset.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Scalability in perception for autonomous driving: Waymo open dataset

Reference 16

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.524908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.524908Z digest=sha256:6157e7153c7bca528f82ab10540b206bc15ee8af46ff2dcae80bc759ec23079f

Observation 10a4c948-27ec-4baa-99dd-3185bfec0c9e · outbound

This paper cites Semantic segmentation network for unstructured rural roads based on improved sppm and fused multiscale features.Applied Sciences, 14(19):8739, 2024.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Semantic segmentation network for unstructured rural roads based on improved sppm and fused multiscale features.Applied Sciences, 14(19):8739, 2024

Reference 17

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.527111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.527111Z digest=sha256:d87949bc2c8017e5a276a2cac812cbc239f976a12b765682b9b3b8e57d97cd07

Observation cd18c12b-2202-48b9-84e4-c34df76291f1 · outbound

This paper cites Construction and enhancement of a rural road instance segmentation dataset based on an improved stylegan2-ada.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Construction and enhancement of a rural road instance segmentation dataset based on an improved stylegan2-ada

Reference 18

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.529543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.529543Z digest=sha256:563b35f9f5b9af33370a083aaaecaca06632214427dd8a278b7bba515e01f886

Observation e5a56f37-b76d-44ed-95d6-bae3124f1cc1 · outbound

This paper cites D$^2$-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation D$^2$-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios

Reference 19

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.549158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.549158Z digest=sha256:ad94834a28a94e4f6cf7e2284344a86722d20627788977802dd537fe9aba3aa3

Observation b4a26dd6-a23d-47ae-9c85-ece36a00ad6d · outbound

This paper cites M4sfwd: A multi-faceted synthetic dataset for remote sensing forest wildfires detection.Expert Systems with Applications, 248:123489, 2024.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation M4sfwd: A multi-faceted synthetic dataset for remote sensing forest wildfires detection.Expert Systems with Applications, 248:123489, 2024

Reference 20

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.568389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.568389Z digest=sha256:26f6b913e69081fc46f28ac5f3dde0a53b4f3a543e13b22f23b955b027ff840c

Observation 80a2415f-2939-4f7a-9087-3a17c94042cd · outbound

This paper cites Rope3d: The roadside perception dataset for autonomous driving and monocular 3d object detection task.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Rope3d: The roadside perception dataset for autonomous driving and monocular 3d object detection task

Reference 21

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.584744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.584744Z digest=sha256:4bfc363b30374b00014414f15cb838b3b02c7bbd3bde9b4840b700822a1dda57

Observation 88a93677-f25e-433d-bc66-2bc16176bfd8 · outbound

This paper cites Detection and tracking meet drones chal- lenge.IEEE transactions on pattern analysis and machine intelligence, 44(11):7380–7399, 2021.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Detection and tracking meet drones chal- lenge.IEEE transactions on pattern analysis and machine intelligence, 44(11):7380–7399, 2021

Reference 22

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.588048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.588048Z digest=sha256:64cd33e172a7578072950ac7990637b0766fe429a203c233f7fba00755d39d1b

Observation afeb4676-4a03-4eb8-ac8e-e11ec30e0011 · outbound

This paper cites Enhancing Object Detection Accuracy in Autonomous Vehicles Using Synthetic Data.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Enhancing Object Detection Accuracy in Autonomous Vehicles Using Synthetic Data

Reference 23

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.590747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.590747Z digest=sha256:234a6157c09fa5aa429e5fdea1e431795090f728ecdd4f3d9e91a106a5afebc6

Observation 3ef06742-ee98-47cc-9fb0-06fed4f68eba · outbound

This paper cites Experimental results on synthetic data generation in unreal engine 5 for real-world object detection.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Experimental results on synthetic data generation in unreal engine 5 for real-world object detection

Reference 24

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.593537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.593537Z digest=sha256:c928b1114da6c72501e639a7db650d7d0477482eaad54c64b819d289e1298201

Observation dabd34d6-dd5c-471c-bf9a-720f8b188d6d · outbound

This paper cites Experimental study on using synthetic images as a portion of training dataset for object recognition in construction site.Buildings, 14(5):1454, 2024.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Experimental study on using synthetic images as a portion of training dataset for object recognition in construction site.Buildings, 14(5):1454, 2024

Reference 25

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.595866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.595866Z digest=sha256:4d2b66140f92b92f4847c9e91be42b50405767fce12a15f260823725c25f2093

Observation e057188a-5c62-4c33-afaf-be907aad71f4 · outbound

This paper cites Optimizing object detection for maritime search and rescue: Progressive fine-tuning of yolov9 with real and synthetic data.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Optimizing object detection for maritime search and rescue: Progressive fine-tuning of yolov9 with real and synthetic data

Reference 26

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.598808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.598808Z digest=sha256:fd464bc922e7bf21dcca9ad69b708fc82429ef42c9259f0cf900f7cfb451494d

Observation 0fd1221f-dee9-4bca-8f92-5aa796a49e42 · outbound

This paper cites Sim2real diffusion: Leveraging foundation vision language models for adaptive automated driving.IEEE Robotics and Automation Letters, 11(1):177– 184, 2025.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Sim2real diffusion: Leveraging foundation vision language models for adaptive automated driving.IEEE Robotics and Automation Letters, 11(1):177– 184, 2025

Reference 27

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.601499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.601499Z digest=sha256:b04219dc274232936cf81890235112928348e9bff68117d31e7d47016bd16d4a

Observation fb99efd2-a0cd-49e2-8923-2c81e7611a9c · outbound

This paper cites Synth it like kitti: Synthetic data generation for object detection in driving scenarios.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Synth it like kitti: Synthetic data generation for object detection in driving scenarios

Reference 28

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.603830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.603830Z digest=sha256:c36616a3171a6d69e3254e73182383eb096b4fa3fc3a1ecc1e71b74c677e27f6

Observation 18c09fa1-8c2e-4b61-9bee-a35cba6f796e · outbound

This paper cites Synthetic data for video surveillance applications of computer vision: A review.Interna- tional Journal of Computer Vision, 132(10):4473–4509, 2024.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Synthetic data for video surveillance applications of computer vision: A review.Interna- tional Journal of Computer Vision, 132(10):4473–4509, 2024

Reference 29

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.606182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.606182Z digest=sha256:174d78b69f9f18f4bc0cfff7759f2e720f0bc139e00bd80691e9415d3b442329

Observation e85c3e6e-2943-4bcb-8b20-dd5ea877fa70 · outbound

This paper cites Object detector differences when using synthetic and real training data: Mg ljungqvist et al.SN computer science, 4(3):302, 2023.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Object detector differences when using synthetic and real training data: Mg ljungqvist et al.SN computer science, 4(3):302, 2023

Reference 30

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.608422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.608422Z digest=sha256:cb5466fe5eadbfa8ce20be6f2d69b1cf8f065ff45eef6296ac4fed2dafac20a7

Observation b55643f7-6855-42b1-b5c7-3a4b9193f0b1 · outbound

This paper cites Pcgod: Enhancing object detection with synthetic data for scarce and sensitive computer vision tasks.IEEE Access, 2025.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Pcgod: Enhancing object detection with synthetic data for scarce and sensitive computer vision tasks.IEEE Access, 2025

Reference 31

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.610966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.610966Z digest=sha256:f8bf60b35d91e8367ef1bffe0ab63b868610ade45fc7ba4f3f0c753756aca581

Observation d9e540a9-4e93-4759-86f6-7c606b370e9d · outbound

This paper cites V olucapture: Multi- view synthetic data capture in unreal engine.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation V olucapture: Multi- view synthetic data capture in unreal engine

Reference 32

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.616373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.616373Z digest=sha256:f7b382f5ed8a9d586ea75ab9ff381aa74773a4073b66caba2e4603b87bc7aab9

Observation f54cf2f9-88d9-4ba6-8234-0611a1a60667 · outbound

This paper cites Syndra: Synthetic dataset for railway applications.

Object Detection for Autonomous Driving in Chinese Rural Scenes: An Experimental Study on Real-Synthetic Data Mixing and Model Evaluation Syndra: Synthetic dataset for railway applications

Reference 33

Resolution
unresolved
no resolver link, observed 2026-07-30T12:27:40.619018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T12:27:40.619018Z digest=sha256:ff9ee44c1c5d27c77e229d3312c3c38bd24299c25e45ae633b95a0d3e796bca4

Pith citing papers

No inbound Pith citation observations are available.