Paper Citation Record · LEDGER

POD: Practical Object Detection with Scale-Sensitive Network

As of 22 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:1909.02225.

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

pith.paper-citation-record.v1
1909.02225 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T05:01:18.776270Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

43 of 43 outbound references displayed

verified exact0
verified fuzzy38
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 54396e21-9d97-45eb-9c9b-dbf29415153e · outbound

This paper cites Cascade r-cnn: Delv- ing into high quality object detection.

POD: Practical Object Detection with Scale-Sensitive Network Cascade r-cnn: Delv- ing into high quality object detection

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.346136Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1214971c-e520-4a13-a03c-4c1187e4ccce · outbound

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

POD: Practical Object Detection with Scale-Sensitive Network Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolu- tion, and fully connected crfs

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.333074Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3f3f6810-ae23-4d00-ac33-eea5571d2aeb · outbound

This paper cites Deformable convolutional networks.

POD: Practical Object Detection with Scale-Sensitive Network Deformable convolutional networks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.319175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2cee310a-34f5-4f00-b7ea-7eea4a014dc6 · outbound

This paper cites DSSD : Deconvolutional Single Shot Detector.

POD: Practical Object Detection with Scale-Sensitive Network DSSD : Deconvolutional Single Shot Detector

Reference 4

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Source-reported events for the cited work

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Observation d2ea03d3-280e-4f57-8643-2dd042621dc7 · outbound

This paper cites Fast r-cnn.

POD: Practical Object Detection with Scale-Sensitive Network Fast r-cnn

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.305665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c005ad61-7950-4636-9f73-cad6fed9b6ed · outbound

This paper cites Rich feature hierarchies for accurate object detection and semantic segmentation.

POD: Practical Object Detection with Scale-Sensitive Network Rich feature hierarchies for accurate object detection and semantic segmentation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.293497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f9176247-8bdf-4608-94e9-d4ef8bef2516 · outbound

This paper cites Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour.

POD: Practical Object Detection with Scale-Sensitive Network Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-14T05:01:18.633545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49f1c5c9-7cbf-4ad5-8451-0a1592ac983c · outbound

This paper cites Rethinking ImageNet Pre-training.

POD: Practical Object Detection with Scale-Sensitive Network Rethinking ImageNet Pre-training

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-14T05:01:18.637743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ada19d86-a6f1-436e-8e58-daca09680881 · outbound

This paper cites Mask r-cnn.

POD: Practical Object Detection with Scale-Sensitive Network Mask r-cnn

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.281159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1d0160a4-7a06-4eaa-ae48-5f6ed2f7bfdb · outbound

This paper cites Delving deep into rectiﬁers: Surpassing human-level perfor- mance on imagenet classiﬁcation.

POD: Practical Object Detection with Scale-Sensitive Network Delving deep into rectiﬁers: Surpassing human-level perfor- mance on imagenet classiﬁcation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.269726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 87d5fb40-bd50-4b4a-b16e-cd4112f00468 · outbound

This paper cites Spatial pyramid pooling in deep convolutional networks for visual recognition.

POD: Practical Object Detection with Scale-Sensitive Network Spatial pyramid pooling in deep convolutional networks for visual recognition

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.257630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 953b97c7-160d-45ae-935a-eb21ce3c6992 · outbound

This paper cites Deep residual learning for image recognition.

POD: Practical Object Detection with Scale-Sensitive Network Deep residual learning for image recognition

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.245473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fe9a9870-3ae7-487b-a826-d24eca2965a8 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

POD: Practical Object Detection with Scale-Sensitive Network MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-14T05:01:18.658337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac141ada-ee12-4284-9fcf-39660ce911fa · outbound

This paper cites Squeeze-and-excitation net- works.

POD: Practical Object Detection with Scale-Sensitive Network Squeeze-and-excitation net- works

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.232972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9eb6e317-485d-4354-a52a-95815d9975dd · outbound

This paper cites Densely connected convolutional net- works.

POD: Practical Object Detection with Scale-Sensitive Network Densely connected convolutional net- works

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.218917Z

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Observation 1cd8d3a6-7c74-4ff6-b933-0a60e939087a · outbound

This paper cites Spatial transformer networks.

POD: Practical Object Detection with Scale-Sensitive Network Spatial transformer networks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.206384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fd2cb160-5b07-421c-9ae2-fcdcf1137d90 · outbound

This paper cites Active convolution: Learning the shape of convolution for image classiﬁcation.

POD: Practical Object Detection with Scale-Sensitive Network Active convolution: Learning the shape of convolution for image classiﬁcation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.193694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3edf87af-67a2-4e37-88e3-738d216606e1 · outbound

This paper cites Acquisition of localization conﬁdence for accurate object detection.

POD: Practical Object Detection with Scale-Sensitive Network Acquisition of localization conﬁdence for accurate object detection

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.180693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7b04c936-ff67-48b7-a3ed-9e328f13e2e1 · outbound

This paper cites Imagenet classiﬁcation with deep convolutional neural net- works.

POD: Practical Object Detection with Scale-Sensitive Network Imagenet classiﬁcation with deep convolutional neural net- works

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.167353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 676e9b5c-ce48-494a-b166-0c599a48699a · outbound

This paper cites Cornernet: Detecting objects as paired keypoints.

POD: Practical Object Detection with Scale-Sensitive Network Cornernet: Detecting objects as paired keypoints

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.155168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a14b3ca8-0a62-4d18-b06a-8dc40f28734a · outbound

This paper cites Detnet: Design backbone for object detection.

POD: Practical Object Detection with Scale-Sensitive Network Detnet: Design backbone for object detection

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.141468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 94b9a61f-a44d-4f62-873c-f702e565b9d2 · outbound

This paper cites Feature pyra- mid networks for object detection.

POD: Practical Object Detection with Scale-Sensitive Network Feature pyra- mid networks for object detection

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.128680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4b0d8d05-e5a1-45a8-bc73-c7fd3024f7de · outbound

This paper cites Focal loss for dense object detection.

POD: Practical Object Detection with Scale-Sensitive Network Focal loss for dense object detection

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.116584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4e843e6c-c577-43b5-848f-85955e40183f · outbound

This paper cites Microsoft coco: Common objects in context.

POD: Practical Object Detection with Scale-Sensitive Network Microsoft coco: Common objects in context

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.103456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8fe0bcb8-dbd9-4eb4-bbda-1dbef58f2768 · outbound

This paper cites Receptive ﬁeld block net for accurate and fast object detection.

POD: Practical Object Detection with Scale-Sensitive Network Receptive ﬁeld block net for accurate and fast object detection

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.091177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 936bf408-ad69-44cb-9e84-fd68d76dce28 · outbound

This paper cites Ssd: Single shot multibox detector.

POD: Practical Object Detection with Scale-Sensitive Network Ssd: Single shot multibox detector

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.078562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 53d7940d-6610-4551-8508-3523909f202c · outbound

This paper cites Megdet: A large mini-batch object detector.

POD: Practical Object Detection with Scale-Sensitive Network Megdet: A large mini-batch object detector

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.065916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 297ab0d6-976e-4d53-9550-1e0e0db8ad7f · outbound

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

POD: Practical Object Detection with Scale-Sensitive Network You only look once: Uniﬁed, real-time object de- tection

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.051022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7212a518-6e50-4f25-809b-8d0ca731e402 · outbound

This paper cites Yolo9000: better, faster, stronger.

POD: Practical Object Detection with Scale-Sensitive Network Yolo9000: better, faster, stronger

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.037903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7281acb6-8dbe-4f97-8250-746974ea9ade · outbound

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

POD: Practical Object Detection with Scale-Sensitive Network Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.025229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8df1cb16-614b-46cb-bdd1-264cdaa66b37 · outbound

This paper cites Imagenet large scale visual recognition challenge.

POD: Practical Object Detection with Scale-Sensitive Network Imagenet large scale visual recognition challenge

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.013067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fc2822a8-6724-4a67-9f6c-de19664d7c4d · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

POD: Practical Object Detection with Scale-Sensitive Network Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:19.000143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 149d0616-f505-43a5-8a31-4eeac30b0edb · outbound

This paper cites Beyond Skip Connections: Top-Down Modulation for Object Detection.

POD: Practical Object Detection with Scale-Sensitive Network Beyond Skip Connections: Top-Down Modulation for Object Detection

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-14T05:01:18.737164Z

Source-reported events for the cited work

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Observation ddb0a0b5-9cdb-4eff-b3cd-f1b8bb27f4fe · outbound

This paper cites Very deep convo- lutional networks for large-scale image recognition.

POD: Practical Object Detection with Scale-Sensitive Network Very deep convo- lutional networks for large-scale image recognition

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:18.986978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 406f2cc5-52c5-4939-bf73-5d16ac3d579a · outbound

This paper cites Going deeper with convolutions.

POD: Practical Object Detection with Scale-Sensitive Network Going deeper with convolutions

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:18.973968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b6ae284d-917f-4887-a505-a9bdec95e5c9 · outbound

This paper cites Improving ob- ject localization with ﬁtness nms and bounded iou loss.

POD: Practical Object Detection with Scale-Sensitive Network Improving ob- ject localization with ﬁtness nms and bounded iou loss

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:18.962155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3080fec8-dc71-4d46-bb67-82a553656eed · outbound

This paper cites Selective search for object recognition.

POD: Practical Object Detection with Scale-Sensitive Network Selective search for object recognition

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:18.949733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0d1c24e7-ed5c-4237-bfc4-95675a1a761b · outbound

This paper cites Aggregated residual transformations for deep neural networks.

POD: Practical Object Detection with Scale-Sensitive Network Aggregated residual transformations for deep neural networks

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:18.935876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 771742d5-83f9-4759-a81d-9fc173cbdab9 · outbound

This paper cites Deep regionlets for object de- tection.

POD: Practical Object Detection with Scale-Sensitive Network Deep regionlets for object de- tection

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:18.922107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cf8ee539-242a-4aaa-9034-7f8a37d0ecff · outbound

This paper cites Multi-scale context aggrega- tion by dilated convolutions.

POD: Practical Object Detection with Scale-Sensitive Network Multi-scale context aggrega- tion by dilated convolutions

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:18.909693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3cba4288-d80d-4fcf-91db-74c3274298de · outbound

This paper cites Scale-adaptive convolutions for scene pars- ing.

POD: Practical Object Detection with Scale-Sensitive Network Scale-adaptive convolutions for scene pars- ing

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:18.896488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c34eface-6682-4554-8e69-752b57c5c9e5 · outbound

This paper cites Single-shot reﬁnement neural network for ob- ject detection.

POD: Practical Object Detection with Scale-Sensitive Network Single-shot reﬁnement neural network for ob- ject detection

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:18.883478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 39e95a96-1dfa-4cdc-8547-45533ccca16a · outbound

This paper cites Pyramid scene parsing network.

POD: Practical Object Detection with Scale-Sensitive Network Pyramid scene parsing network

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:01:18.870013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.