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Paper Citation Record · LEDGER

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation

As of 16 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:1908.08652.

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

pith.paper-citation-record.v1
1908.08652 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:36:36.878498Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

24 of 24 outbound references displayed

  • verified exact0
  • verified fuzzy22
  • unresolved1
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b0890813-0976-40c3-beff-f09318db5d9a · outbound

This paper cites It could hel p to prevent traffic congestion and stampedes at crowded events.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation It could hel p to prevent traffic congestion and stampedes at crowded events

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.279117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.762752Z digest=sha256:e63b6fe92f2ffb9d655b3b948d43abbd21e522a1f113f8c4ce30bc28617a33c2

Observation 4fff192a-d229-494c-9017-cfad4fec9c77 · outbound

This paper cites Crowd Density Estimation.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Crowd Density Estimation

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.264681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.768742Z digest=sha256:415676da335d85c98660c044e4d86da47cb94d992c823c61785c4da6e669781b

Observation 1b48746c-4af3-47c7-99e7-0c3e4387b87a · outbound

This paper cites ShanghaiTech dataset The ShanghaiTech dataset [9] comprises 1198 annotat ed images with to tal 330,165 people in them.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation ShanghaiTech dataset The ShanghaiTech dataset [9] comprises 1198 annotat ed images with to tal 330,165 people in them

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.249271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.774175Z digest=sha256:71dcb0a0e18037b2a5194c5d353523cfd71237cdceeb2e4723914104ab0e1f12

Observation 5f0f516c-dd76-45b4-8f6d-e78fe536f227 · outbound

This paper cites MTCNet outperforms them all on two benchmark datasets in terms of Mean Absolute Error (MAE) and Mean Squa red Error (MSE).

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation MTCNet outperforms them all on two benchmark datasets in terms of Mean Absolute Error (MAE) and Mean Squa red Error (MSE)

Reference 4

Resolution
malformed identifier
raw_fallback, observed 2026-08-14T11:36:37.233899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.779312Z digest=sha256:5b826d1481817cbafce1ff7603051de66577beae21b10db2d45f5eeb39623501

Observation 8ed8805a-a72f-4e87-9952-3facd3aa4ae0 · outbound

This paper cites an unresolved cited work.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Unresolved cited work

Reference 5

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unresolved
raw_fallback, observed 2026-08-14T11:36:37.218688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.784964Z digest=sha256:ab5e2309bcb1036da99e89cef6c26e94ba95a86eb00493d06dfeca49e51cfcfa

Observation bb7aedb2-2bd9-44a9-a415-602241c60da8 · outbound

This paper cites Histograms of oriented gradients for human detection,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Histograms of oriented gradients for human detection,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.203647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.790286Z digest=sha256:12e3bea5daa08d46df3a6d634219894956aac81c0caeced7f5c02e1317797d2e

Observation 49a5fe9f-3127-4a8f-9d78-99a4e006db2f · outbound

This paper cites Bayesian poisson regression for crowd counting,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Bayesian poisson regression for crowd counting,

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.188593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.795246Z digest=sha256:2a4d90661fd331cba0ad79dfdf720793bed51b0923102dcb1375778535c249f3

Observation 9c55ccfb-3f4a-4cbc-865d-297e92407480 · outbound

This paper cites Crowd density estimation based on rich features and random projection forest,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Crowd density estimation based on rich features and random projection forest,

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.173338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.800028Z digest=sha256:858cde58714e5516d793ec20cc8bb71578d391acf9610d248fbb4c3250f1a3eb

Observation 051eeeb2-286e-4ad9-99f3-8846d5604491 · outbound

This paper cites Learning to count objects in images,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Learning to count objects in images,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.157426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.805474Z digest=sha256:02609c091b6e0e6a922bbc462454c1fd9e7053b697d8efa84e0f68c583902959

Observation ea412bb2-3295-4850-bb35-2c71f3719d18 · outbound

This paper cites COUNT Forest: CO -Voting Uncertain Number of Targets Using Random Forest for Crowd Density Estimation,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation COUNT Forest: CO -Voting Uncertain Number of Targets Using Random Forest for Crowd Density Estimation,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.141995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.810105Z digest=sha256:ead42c5584ab97f822b0b3bf20749e5cc275236d63b3d466c95c4804d30e20d2

Observation 74e1ec10-3ed6-4a91-997e-2e3daea81f51 · outbound

This paper cites Deep people counting in extremely dense crowds,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Deep people counting in extremely dense crowds,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.124733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.815003Z digest=sha256:25abf89a353add895561cc47856f31bc1837f8d77f1b1ad707c6e03dee48d200

Observation 77c6dd60-6674-493e-a494-26c208c4c192 · outbound

This paper cites Learning to count with cnn boosting,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Learning to count with cnn boosting,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.109882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.820165Z digest=sha256:08deb5a67d4262dc6a59eca8b2253aa94a53c22f23b8adeff1affb5291241743

Observation 18d4a7e3-2970-40f7-87a7-fc5ce14abf6d · outbound

This paper cites Cross-scene crowd counting via deep co nvolutional neural networks,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Cross-scene crowd counting via deep co nvolutional neural networks,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.095466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.824586Z digest=sha256:fff41d1a371d34caa5c5de198c27fc503b08d77dde39d0a369afe13a10e8698e

Observation 7c373999-0168-49ae-8874-e6f38b0d5574 · outbound

This paper cites Single - Image Crowd Counting via Multi -Column Convolutional Neural Network,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Single - Image Crowd Counting via Multi -Column Convolutional Neural Network,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.080302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.829380Z digest=sha256:f7501bdb1763d602c712024525b4997654ff4552e60281a44980247457c1fa98

Observation 9934aa61-909f-4982-bc70-dd73dc75e6bf · outbound

This paper cites Switching Convolutional Neural Network for Crowd Counting,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Switching Convolutional Neural Network for Crowd Counting,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.064529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.834000Z digest=sha256:9d0edc89abb9cd4079013e4180652d872bdc9e86488947a8dcdff83736ab5a37

Observation aadb4ea4-5895-4923-b908-ee371d64ec3a · outbound

This paper cites CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes,

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.049079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.838546Z digest=sha256:d43d605e39794c4a78d0498411dcf346633c742c04fa7a0aeee7cd5e7109a957

Observation c1656b50-593e-4724-856b-2b232a3eac12 · outbound

This paper cites Multitask learning,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Multitask learning,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.032831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.843873Z digest=sha256:febc33594612e053f32c24b57aa48b11340e08e315221e518552818fa6bd3d35

Observation 4e412376-0c0b-4e30-9874-89b9c19594c6 · outbound

This paper cites Very deep convolutional networks for large -scale image recognition,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Very deep convolutional networks for large -scale image recognition,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:37.017051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.848542Z digest=sha256:afb691ee2505fa695e65daca1827188b9e454a6d0f07885c4d67ce194c75c452

Observation 5e41bd02-8b76-447a-bcdf-87a94b7a88da · outbound

This paper cites Multi -scale context aggregation by dilated convolutions,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Multi -scale context aggregation by dilated convolutions,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:36.999618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.853426Z digest=sha256:f4f88fcf9d4a6e7c6118c9eaec67300b9fc5de8a8a508de6a994fe638cdfb067

Observation 479243d3-d131-4d72-9eb9-e439d81d5f23 · outbound

This paper cites Exploiting Unrelated Tasks in Multi -Task Learning,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Exploiting Unrelated Tasks in Multi -Task Learning,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:36.982142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.858968Z digest=sha256:d0a8c9f5db20e17153e70b08c71771c0ed1caeba0f195ada782f6023cb541214

Observation dfbf8f82-7188-4ea4-8db7-daf279ce69d0 · outbound

This paper cites Mul ti-source Multi-scale Counting in Extremely Dense Crowd Images,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Mul ti-source Multi-scale Counting in Extremely Dense Crowd Images,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:36.965770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.863644Z digest=sha256:cd99e278ea7df3892ce1a41ec32bb41d31be50846ef37faf682d631253525556

Observation d2841158-6939-46a0-9fd3-c4ea769edc4f · outbound

This paper cites Multi -scale convolutional neural networks fo r crowd counting,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Multi -scale convolutional neural networks fo r crowd counting,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:36.949857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.868699Z digest=sha256:d0bfda88022ced421b3ae2db7af4e80b769be1a555ea1a67c9a2c6dbc74c2eb8

Observation de78d5a3-80ff-4043-b3e4-56d31a077d9b · outbound

This paper cites Leveraging Unlabeled Data for Crowd Counting by Learning to Rank,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Leveraging Unlabeled Data for Crowd Counting by Learning to Rank,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:36.933734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.873556Z digest=sha256:b8862c32c159537348736f1d0fa96f3c799fb0211a479fbc8efc20022a7977a6

Observation 3a20010a-8b72-442d-8bc5-287532ca6b60 · outbound

This paper cites Crowd Counting with Fully Convolutional Neural Network,.

MTCNET: Multi-task Learning Paradigm for Crowd Count Estimation Crowd Counting with Fully Convolutional Neural Network,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:36:36.917099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T11:36:36.878498Z digest=sha256:0469ecdae629784f2be4b9d6ac3f694e667b5b368322bf9728e69967c43f70c7

Pith citing papers

No inbound Pith citation observations are available.