Paper Citation Record · LEDGER

Investigating Convolutional Neural Networks using Spatial Orderness

As of 16 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:1908.06416.

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

pith.paper-citation-record.v1
1908.06416 v2

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:52:14.032901Z

measured 16 of 16 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

16 of 16 outbound references displayed

verified exact0
verified fuzzy9
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5751081e-b739-40ba-a847-1da6d8416cd8 · outbound

This paper cites Scaling learning algorithms towards AI.

Investigating Convolutional Neural Networks using Spatial Orderness Scaling learning algorithms towards AI

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:52:14.216482Z

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 e7904613-385e-434f-845a-cf3e9914fca8 · outbound

This paper cites Representation learning: A review and new perspectives.

Investigating Convolutional Neural Networks using Spatial Orderness Representation learning: A review and new perspectives

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T12:52:13.978149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f81fda1-0045-4a58-a304-093e0293d3fb · outbound

This paper cites Approximating CNNs with bag-of-local- features models works surprisingly well on ImageNet.

Investigating Convolutional Neural Networks using Spatial Orderness Approximating CNNs with bag-of-local- features models works surprisingly well on ImageNet

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:52:14.205931Z

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 f6e866f7-cc3d-4716-b0eb-bd6f03225bcf · outbound

This paper cites He et al.

Investigating Convolutional Neural Networks using Spatial Orderness He et al

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T12:52:13.985690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3da2436-6547-49a5-8c9b-35b65b08c6c5 · outbound

This paper cites Measuring the tendency of CNNs to Learn Surface Statistical Regularities.

Investigating Convolutional Neural Networks using Spatial Orderness Measuring the tendency of CNNs to Learn Surface Statistical Regularities

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-14T12:52:13.989552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31af8b7e-16b3-4150-a11a-337916496a20 · outbound

This paper cites Generalization in deep learning.

Investigating Convolutional Neural Networks using Spatial Orderness Generalization in deep learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:52:14.194303Z

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 1dd58e85-56a8-490f-bcaf-a485dfd6c02d · outbound

This paper cites Learning multiple layers of features from tiny images.

Investigating Convolutional Neural Networks using Spatial Orderness Learning multiple layers of features from tiny images

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:52:14.182636Z

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 dbb62da3-e07c-4d35-bb85-f2189a079f67 · outbound

This paper cites an unresolved cited work.

Investigating Convolutional Neural Networks using Spatial Orderness Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-14T12:52:14.171327Z

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 60da2687-c3fa-4f18-b182-9e3efc6b805f · outbound

This paper cites Understanding the effective receptive ﬁeld in deep convolutional neural networks.

Investigating Convolutional Neural Networks using Spatial Orderness Understanding the effective receptive ﬁeld in deep convolutional neural networks

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:52:14.159853Z

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 93972012-aac1-4a9e-aedb-816b9357b0e5 · outbound

This paper cites an unresolved cited work.

Investigating Convolutional Neural Networks using Spatial Orderness Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-14T12:52:14.149060Z

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 75fa7258-1e71-4b50-9a2a-81dae5f85f98 · outbound

This paper cites Simonyan and A.

Investigating Convolutional Neural Networks using Spatial Orderness Simonyan and A

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T12:52:14.013432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 563441d7-fe41-4f88-83da-fcc136c4a72c · outbound

This paper cites On the depth of deep neural networks: A theoretical view.

Investigating Convolutional Neural Networks using Spatial Orderness On the depth of deep neural networks: A theoretical view

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:52:14.132235Z

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 61e8398b-7a98-41bc-b0cc-f76b75d0b4a9 · outbound

This paper cites Regularization of neural networks using dropconnect.

Investigating Convolutional Neural Networks using Spatial Orderness Regularization of neural networks using dropconnect

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:52:14.120734Z

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 f02fea14-e922-420c-9477-40c8fd592c07 · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Investigating Convolutional Neural Networks using Spatial Orderness Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T12:52:14.024884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4607cf5-5a60-43ec-8cf7-9b0b077db65c · outbound

This paper cites Zeiler and Rob Fergus.

Investigating Convolutional Neural Networks using Spatial Orderness Zeiler and Rob Fergus

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:52:14.108411Z

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 aac0a3fa-f748-4067-9ac2-57a025f921f5 · outbound

This paper cites effective.

Investigating Convolutional Neural Networks using Spatial Orderness effective

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T12:52:14.096208Z

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.

Pith citing papers

No inbound Pith citation observations are available.