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Paper Citation Record · LEDGER

X-ray illicit object detection using hybrid CNN-transformer neural network architectures

As of 17 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2505.00564.

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

pith.paper-citation-record.v1
2505.00564 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:42:15.195998Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

35 of 35 outbound references displayed

  • verified exact0
  • verified fuzzy26
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 77e3ac66-436f-442d-9578-b8dae1933f24 · outbound

This paper cites Pidray: A large-scale x- ray benchmark for real-world prohibited item detection,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Pidray: A large-scale x- ray benchmark for real-world prohibited item detection,

Reference 1

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation e3bd91b6-f695-409c-9da4-96831ea536a4 · outbound

This paper cites Illicit item detection in x-ray images for security applications,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Illicit item detection in x-ray images for security applications,

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 3855ecc8-6220-45dd-a7a2-6981e51bc922 · outbound

This paper cites Computer vision on x-ray data in industrial production and security applications: A comprehensive survey,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Computer vision on x-ray data in industrial production and security applications: A comprehensive survey,

Reference 3

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 4fdde472-b0b3-4c94-8580-e9d8068bc987 · outbound

This paper cites Visual inspection for illicit items in x-ray images using deep learn- ing,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Visual inspection for illicit items in x-ray images using deep learn- ing,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.052893Z digest=sha256:ce11449580c851b66c2ba72b7dc821f548626601b4c129cc9903919852b6652a

Observation 38438511-c2a8-4d43-8300-04b76d9693ab · outbound

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

X-ray illicit object detection using hybrid CNN-transformer neural network architectures An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:42:15.058456Z digest=sha256:19463df71d6ea547fc2e8a7a5591eedc083e979e5eb64f99b1cef85637bb234f

Observation e04b334e-d87b-48bb-8233-c1c9069b426e · outbound

This paper cites Illicit object detection in x-ray images using vision transformers,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Illicit object detection in x-ray images using vision transformers,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.063317Z digest=sha256:4ef9728c5a481d310dc6ebc38c38e7476c8d8a6a7abc34eda84b4e18ec214e34

Observation 71576436-a930-4991-ab8b-79bba5532926 · outbound

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

X-ray illicit object detection using hybrid CNN-transformer neural network architectures End-to-end object detection with transformers,

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:42:15.068584Z digest=sha256:c92675b7a158ec4704b1b41451c433dc64e172797b27f97534248073e47d8c6f

Observation a3f4c213-e002-4f79-9ace-9744bce85fa1 · outbound

This paper cites Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity

Reference 8

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source=pdf_text observed=2026-08-16T04:42:15.073101Z digest=sha256:6dc7f1e56a071d4c5363ad7fadb3aec2485e6d68782aa5095b0eed81ca5e2b54

Observation 2466f2a4-92a8-4015-9206-74330fd1eefc · outbound

This paper cites DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

Reference 9

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source=pdf_text observed=2026-08-16T04:42:15.078105Z digest=sha256:7d8e714b73fee188a32a4f86b56d6b125a8733e84582b30d1e365bf2b5cf7616

Observation 17f9f903-eb78-4c62-89fb-a98d7faf15db · outbound

This paper cites Advances in diffusion models for image data augmentation: A review of methods, models, evaluation metrics and future research directions,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Advances in diffusion models for image data augmentation: A review of methods, models, evaluation metrics and future research directions,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.083016Z digest=sha256:5db3c36f385fa59c968e70f829ec4500d69d125fe8f42aca567afdb20d045301

Observation ff98c676-c98c-456b-98d9-456bb559aa79 · outbound

This paper cites A survey of the vision transformers and their cnn-transformer based variants,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures A survey of the vision transformers and their cnn-transformer based variants,

Reference 11

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source=pdf_text observed=2026-08-16T04:42:15.087773Z digest=sha256:01d45dc94af1411621b543926f6809a4f9b165a09b8f0a59ec26eb2124728d77

Observation aa8a1de3-bd8f-458a-a680-d8b78315cecf · outbound

This paper cites Combining transformer and cnn for object detection in uav imagery,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Combining transformer and cnn for object detection in uav imagery,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.092020Z digest=sha256:c83eaf81dbc130d366927b8fe549469b244ae51c58a41de6794aae405ad5693a

Observation b94cfe39-0896-4723-bad5-acefd02857f2 · outbound

This paper cites Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:42:15.097008Z digest=sha256:c2737afe84cf87c4e6eb8ac4e243ae6720c169218176c649233b65c8120f8dcc

Observation 76f5b287-eff6-4d68-babd-d37e104a2896 · outbound

This paper cites Object detection and x-ray security imaging: A survey,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Object detection and x-ray security imaging: A survey,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.101793Z digest=sha256:c78fe4eac80318a0ca490c7fab2902160bfe117d0937c23a2fb8c21bca5f00ac

Observation 1fe37a67-8b7e-421d-954f-2f538283e135 · outbound

This paper cites The invisible arms race: digital trends in illicit goods trafficking and ai-enabled responses,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures The invisible arms race: digital trends in illicit goods trafficking and ai-enabled responses,

Reference 15

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.106463Z digest=sha256:abef750ccc9763e7d245595fef145457875238d72073bbfb88b30ff01c062315

Observation 7c58b27b-d67d-437e-be94-8350a93312c7 · outbound

This paper cites an unresolved cited work.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Unresolved cited work

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.110990Z digest=sha256:78d87b30d5216e8e7f840975b9412874d02c68ec0f0f631a5040ce0008ee89b0

Observation c46f0a89-29af-495d-830d-9c3f17ec4ce7 · outbound

This paper cites Jocher, J.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Jocher, J

Reference 17

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 4e6e463f-50fd-4170-b658-f56efb303392 · outbound

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

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Detrs beat yolos on real-time object detection,

Reference 18

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 29bb6ab6-4762-4a4c-bf00-0d32034bd7d8 · outbound

This paper cites Exploring endogenous shift for cross-domain detection: A large-scale benchmark and perturbation suppression network,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Exploring endogenous shift for cross-domain detection: A large-scale benchmark and perturbation suppression network,

Reference 19

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 37453e04-c898-4916-b371-a7f89d40abec · outbound

This paper cites Towards real-world x-ray security inspection: A high-quality benchmark and lateral inhibition module for prohibited items detection,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Towards real-world x-ray security inspection: A high-quality benchmark and lateral inhibition module for prohibited items detection,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 0f40f1f0-8079-48e4-8b30-16a1b687da8c · outbound

This paper cites Towards real- world prohibited item detection: A large-scale x-ray benchmark,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Towards real- world prohibited item detection: A large-scale x-ray benchmark,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.134275Z digest=sha256:b5332f08d9f2ceee59cd8f4148561589e603f6441df046d743af81b864c4ce56

Observation 14e1f633-f273-40d6-92c3-8a04679bc621 · outbound

This paper cites Occluded prohibited items detection: An x-ray security inspection benchmark and de-occlusion attention module,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Occluded prohibited items detection: An x-ray security inspection benchmark and de-occlusion attention module,

Reference 22

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.139130Z digest=sha256:e81869768d011977455ecf11a5c80d7049e72861bf48be0a9dde05f4663ebc9a

Observation 727aa156-fdee-452a-aa86-271ace85f616 · outbound

This paper cites Em-yolo: An x-ray prohibited- item-detection method based on edge and material information fusion,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Em-yolo: An x-ray prohibited- item-detection method based on edge and material information fusion,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.143667Z digest=sha256:9569d16c6e174368009547b1fd7a2b704b55228556d000a28c70bd77599ff24d

Observation 7d3b3bf0-2aba-4f37-9ed1-e1c807ee5d1f · outbound

This paper cites Sc-yolov8: A security check model for the inspection of prohibited items in x-ray images,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Sc-yolov8: A security check model for the inspection of prohibited items in x-ray images,

Reference 24

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.148243Z digest=sha256:3597dc4356bfdcf44df6a3d60d0afb4f7b8cfa9fe186902baf3f25583e9bd57f

Observation 5bbc289e-f852-4a92-83af-e2a54e07a9a8 · outbound

This paper cites Lightweight detection method for x-ray security inspection with occlusion,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Lightweight detection method for x-ray security inspection with occlusion,

Reference 25

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 61930377-4416-4362-9b6c-b2f6d31a9595 · outbound

This paper cites Improved yolov8 for dangerous goods detection in x-ray security images,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Improved yolov8 for dangerous goods detection in x-ray security images,

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.156794Z digest=sha256:4e70c7e2c37bd47508feaba5af2b616555ff4ed6831d3645f99145b82d4e57fe

Observation 5580067c-93f4-42d3-a3bd-da8c28605738 · outbound

This paper cites Lightweight prohibited items detection model in x-ray images based on improved yolov7-tiny,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Lightweight prohibited items detection model in x-ray images based on improved yolov7-tiny,

Reference 27

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.161075Z digest=sha256:a49682c803a35a561c3056a6eafcead53dbecfe943ed4e2d064beb55f0fa4468

Observation de9370bc-c480-4d0d-8b78-3dfbf9d253f7 · outbound

This paper cites Fea- ture knowledge distillation-based model lightweight for prohibited item detection in x-ray security inspection images,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Fea- ture knowledge distillation-based model lightweight for prohibited item detection in x-ray security inspection images,

Reference 28

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.165494Z digest=sha256:89147ea1462de0765bb9174479401e4f85c40e6b84617ff68926a5d127ff2ac7

Observation e51e5401-96ad-48f9-b9b9-ee161df1ec31 · outbound

This paper cites Transformer-based dual-view x-ray security inspection image analysis,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Transformer-based dual-view x-ray security inspection image analysis,

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:42:15.169864Z digest=sha256:52fac3e270a8fb9c0595e20933939d0217eb8baa25cc4b8d5a26b535285f3f16

Observation 0823599f-41d7-4b2d-9fe9-8f15b34a0190 · outbound

This paper cites Eslaxdet: A new x-ray baggage security detection framework based on self-supervised vision transformers,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Eslaxdet: A new x-ray baggage security detection framework based on self-supervised vision transformers,

Reference 30

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raw_fallback, observed 2026-08-16T04:42:15.363603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.174083Z digest=sha256:22ae4f3507ff940bfcde91b08c8fe7614dee4852884587a6df41163a35b3976a

Observation 26010cf4-9f0f-420e-b32a-03d785d413ad · outbound

This paper cites Self-supervised visual learning in the low-data regime: a comparative evaluation,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Self-supervised visual learning in the low-data regime: a comparative evaluation,

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.178358Z digest=sha256:32e0dcf5f2ef1968b5dd0dbe605b176a30f95ab13552a16a0e809c79f51ea943

Observation 2d9d8e8d-e6c6-4730-a771-a52a0b9fcf63 · outbound

This paper cites Tinyvit: Fast pretraining distillation for small vision transformers,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Tinyvit: Fast pretraining distillation for small vision transformers,

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.182493Z digest=sha256:7056b4d3a5567716272eeab7325fd9842f0cea3e07ad49395144caa5a528705c

Observation c86cd98e-c8ce-4856-98ee-9a12a8a55bdb · outbound

This paper cites Detection of novel prohibited item categories for real-world security inspection,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Detection of novel prohibited item categories for real-world security inspection,

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T04:42:15.187205Z digest=sha256:83634e4e867fe7395e033ffc520f56970543f8fe108e65c3e4c8730e8f326539

Observation 89bba91d-7484-4bec-b383-a4c55a607010 · outbound

This paper cites Adaptxray: Vision transformer and adapter in x-ray images for prohibited items detection,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Adaptxray: Vision transformer and adapter in x-ray images for prohibited items detection,

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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This paper cites Microsoft coco: Common objects in context,.

X-ray illicit object detection using hybrid CNN-transformer neural network architectures Microsoft coco: Common objects in context,

Reference 35

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source=pdf_text observed=2026-08-16T04:42:15.195998Z digest=sha256:b51be0a50fc995c3e316f89878ed7b797c0d4ead7357e4a6d1362ceff0cf4dfc

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