Paper Citation Record · LEDGER

A Comparison of CNN and Classic Features for Image Retrieval

As of 16 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:1908.09300.

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

pith.paper-citation-record.v1
1908.09300 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:18:52.881524Z

measured 23 of 23 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

23 of 23 outbound references displayed

verified exact1
verified fuzzy15
unresolved5
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 36d765c1-3c19-4da9-83a2-a1c130d37f86 · outbound

This paper cites Recent advances in features extraction and description algorithms: A comprehensive survey,.

A Comparison of CNN and Classic Features for Image Retrieval Recent advances in features extraction and description algorithms: A comprehensive survey,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.543001Z

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.

Observation f6d26a77-b211-41a5-b706-67cda93889b2 · outbound

This paper cites A survey of recent advances in visual feature detection,.

A Comparison of CNN and Classic Features for Image Retrieval A survey of recent advances in visual feature detection,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.525605Z

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.

Observation d6d913d9-761d-484d-8cd8-4bd9de39b803 · outbound

This paper cites Distinctive image features from scale-invariant keypoints,.

A Comparison of CNN and Classic Features for Image Retrieval Distinctive image features from scale-invariant keypoints,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T11:18:52.689892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c794853-dbdc-4f00-9944-bc97a66a6122 · outbound

This paper cites Speeded-up robust features (surf),.

A Comparison of CNN and Classic Features for Image Retrieval Speeded-up robust features (surf),

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T11:18:52.698198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93989fde-50ea-4fee-bdfa-2617cf70f685 · outbound

This paper cites Brisk: Binary robust invariant scalable keypoints,.

A Comparison of CNN and Classic Features for Image Retrieval Brisk: Binary robust invariant scalable keypoints,

Reference 6

Resolution: malformed identifier; no resolver link, observed 2026-08-14T11:18:52.715872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ebeb5cd-a8f2-4cf1-b00b-2b07bc406301 · outbound

This paper cites Freak: Fast retina keypoint,.

A Comparison of CNN and Classic Features for Image Retrieval Freak: Fast retina keypoint,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.473756Z

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.

Observation 260c3e2b-f2f7-4335-b9a5-70535960bb02 · outbound

This paper cites Learning covariant feature detectors,.

A Comparison of CNN and Classic Features for Image Retrieval Learning covariant feature detectors,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.455841Z

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.

Observation 6ac576ca-ed93-42e4-a912-54f0bdc60fdb · outbound

This paper cites Tilde: A temporally invariant learned detector,.

A Comparison of CNN and Classic Features for Image Retrieval Tilde: A temporally invariant learned detector,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.434945Z

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.

Observation ef221e95-9c8a-48c3-ac29-212242edfc35 · outbound

This paper cites Quad- networks: unsupervised learning to rank for interest point detection,.

A Comparison of CNN and Classic Features for Image Retrieval Quad- networks: unsupervised learning to rank for interest point detection,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.406876Z

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.

Observation c5a3a9b6-d87b-4448-bd22-f2ef6a373d6e · outbound

This paper cites LIFT: Learned Invariant Feature Transform,.

A Comparison of CNN and Classic Features for Image Retrieval LIFT: Learned Invariant Feature Transform,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.384598Z

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.

Observation f99d0edf-37ae-4955-827a-9c744573fe8e · outbound

This paper cites Learning to assign orientations to feature points,.

A Comparison of CNN and Classic Features for Image Retrieval Learning to assign orientations to feature points,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.364483Z

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.

Observation c2d914c7-fc71-476e-b0e1-a7fd6817578e · outbound

This paper cites Extracting semantic information from visual data: A survey,.

A Comparison of CNN and Classic Features for Image Retrieval Extracting semantic information from visual data: A survey,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.342866Z

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.

Observation 448adb16-252d-45b2-a27b-dff0ccffadf3 · outbound

This paper cites Agrawal, K.

A Comparison of CNN and Classic Features for Image Retrieval Agrawal, K

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.318818Z

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.

Observation 04804f01-500b-4028-a682-7806a6a9bc14 · outbound

This paper cites Adaptive and generic corner detection based on the accelerated segment test,.

A Comparison of CNN and Classic Features for Image Retrieval Adaptive and generic corner detection based on the accelerated segment test,

Reference 15

Resolution: metadata mismatch; raw_fallback, observed 2026-08-14T11:18:53.098388Z

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.

Observation ef0c0ff7-1225-44af-bc3d-a05e28fa200e · outbound

This paper cites Machine learning for high-speed corner detection,.

A Comparison of CNN and Classic Features for Image Retrieval Machine learning for high-speed corner detection,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.297589Z

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.

Observation 1337b6ce-68a3-4291-a67f-8a7eb35043f7 · outbound

This paper cites Mea- suring the coverage of interest point detectors,.

A Comparison of CNN and Classic Features for Image Retrieval Mea- suring the coverage of interest point detectors,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.276530Z

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.

Observation ea3d8d30-3e7e-4c49-8918-2669e28ab795 · outbound

This paper cites Is repeatability an unbiased criterion for ranking feature detectors?.

A Comparison of CNN and Classic Features for Image Retrieval Is repeatability an unbiased criterion for ranking feature detectors?

Reference 19

Resolution: verified exact; doi, observed 2026-08-14T11:18:52.936053Z

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.

Observation b0921dd2-b8aa-4119-826a-f13b405abbb7 · outbound

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

A Comparison of CNN and Classic Features for Image Retrieval Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-14T11:18:52.858257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8134b57-0b09-4b2b-91e1-0641055fc672 · outbound

This paper cites Sift meets cnn: A decade survey of instance retrieval,.

A Comparison of CNN and Classic Features for Image Retrieval Sift meets cnn: A decade survey of instance retrieval,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.255017Z

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.

Observation 92863175-5563-436c-9055-810273be5342 · outbound

This paper cites Video google: a text retrieval approach to object matching in videos,.

A Comparison of CNN and Classic Features for Image Retrieval Video google: a text retrieval approach to object matching in videos,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T11:18:52.868661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16189be0-f94c-4b70-a1f4-56390eb9a4d0 · outbound

This paper cites Interesting interest points,.

A Comparison of CNN and Classic Features for Image Retrieval Interesting interest points,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.218880Z

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.

Observation 33944c65-d25e-46f7-85bd-4b7b0c788956 · outbound

This paper cites TensorFlow: Large-scale machine learning on heterogeneous systems,.

A Comparison of CNN and Classic Features for Image Retrieval TensorFlow: Large-scale machine learning on heterogeneous systems,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:18:53.195790Z

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.

Observation 699f0c2c-60dd-4374-9f86-03566ec9f3a3 · outbound

This paper cites Particular object retrieval with integral max-pooling of CNN activations.

A Comparison of CNN and Classic Features for Image Retrieval Particular object retrieval with integral max-pooling of CNN activations

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-14T11:18:52.826642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.