Paper Citation Record · LEDGER

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification

As of 5 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:1907.01803.

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

pith.paper-citation-record.v1
1907.01803 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-25T10:06:09.208350Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+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

19 of 19 outbound references displayed

verified exact3
verified fuzzy16
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 496f2cdf-6ed0-4345-8691-761bf1ee4015 · outbound

This paper cites Deep residual learning for image recognition.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification Deep residual learning for image recognition

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.152748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b2ffb017-21ec-485e-a486-b7198e62bf5a · outbound

This paper cites Densely connected convolutional networks.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification Densely connected convolutional networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.140814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5f102041-f0e2-4ef8-a78b-109b9ce073f9 · outbound

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

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-25T10:06:52.019790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1534e7f3-df42-46ec-a417-6b3c8b8cfeac · outbound

This paper cites CP-JKU sub- missions for DCASE-2016: A hybrid approach using binaural i-vectors and deep convolutional neural networks.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification CP-JKU sub- missions for DCASE-2016: A hybrid approach using binaural i-vectors and deep convolutional neural networks

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.153002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1c12bc7c-24ff-461c-929a-7850be2f2f11 · outbound

This paper cites Classifying short acoustic scenes with I-vectors and CNNs: Challenges and optimisations for the 2017 DCASE ASC task.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification Classifying short acoustic scenes with I-vectors and CNNs: Challenges and optimisations for the 2017 DCASE ASC task

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.131408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fab7021f-aedc-40e9-91ad-ff6b794ab727 · outbound

This paper cites Acoustic Scene Classiﬁcation with Fully Convolutional Neural Networks and I-Vectors.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification Acoustic Scene Classiﬁcation with Fully Convolutional Neural Networks and I-Vectors

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.155519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 16018d11-0775-4f25-8ec5-f3df29d93b6b · outbound

This paper cites Acoustic Scene Classiﬁcation by Ensemble of Spectrograms Based on Adaptive Temporal Divisions.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification Acoustic Scene Classiﬁcation by Ensemble of Spectrograms Based on Adaptive Temporal Divisions

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.125856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6640df33-dba9-455e-80a3-a55406b3f42b · outbound

This paper cites CNN architectures for large-scale audio classiﬁcation.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification CNN architectures for large-scale audio classiﬁcation

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.160927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4c54be51-e9e7-4fe8-97dc-903d8edfea10 · outbound

This paper cites Training general-purpose audio tagging networks with noisy labels and iterative self-veriﬁcation.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification Training general-purpose audio tagging networks with noisy labels and iterative self-veriﬁcation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.149865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8b0aeb76-5be0-473b-af2b-4f325f7d1b38 · outbound

This paper cites Stacked Convolutional Neural Networks for General-purpose Audio Tagging.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification Stacked Convolutional Neural Networks for General-purpose Audio Tagging

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.146401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 56179355-39a7-44e7-8190-7b5346672a9a · outbound

This paper cites Ensemble of Convolutional Neural Networks for Weakly-Supervised Sound Event Detection Using Multiple Scale Input.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification Ensemble of Convolutional Neural Networks for Weakly-Supervised Sound Event Detection Using Multiple Scale Input

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.139867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation aaf44371-9881-48c2-a8da-a0b20571e878 · outbound

This paper cites Iterative knowledge distillation in R-CNNs for weakly-labeled semi-supervised sound event detection.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification Iterative knowledge distillation in R-CNNs for weakly-labeled semi-supervised sound event detection

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.158242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4164242b-8e41-4f1e-82d6-d324adb74259 · outbound

This paper cites Experimenting with musically motivated convolutional neural networks.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification Experimenting with musically motivated convolutional neural networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.149619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9ca93881-f54b-49bf-9bcc-d33e6252a23c · outbound

This paper cites Understanding the Effective Receptive Field in Deep Convolutional Neural Networks.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification Understanding the Effective Receptive Field in Deep Convolutional Neural Networks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.146941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 575385a5-172e-4972-95de-e4a6006f3196 · outbound

This paper cites TUT database for acoustic scene classiﬁcation and sound event detection.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification TUT database for acoustic scene classiﬁcation and sound event detection

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.163480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9afd6956-708a-4340-98fa-97802e6b2303 · outbound

This paper cites DCASE 2017 challenge setup: Tasks, datasets and baseline system.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification DCASE 2017 challenge setup: Tasks, datasets and baseline system

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.166286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 27b552e7-8de7-4f09-a767-821ee70c663f · outbound

This paper cites A multi-device dataset for urban acoustic scene classiﬁcation.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification A multi-device dataset for urban acoustic scene classiﬁcation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T10:06:52.169368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5cef4147-7677-4a39-afec-1fc1971c1a8d · outbound

This paper cites Adam: A Method for Stochastic Optimization.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification Adam: A Method for Stochastic Optimization

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-05-25T10:06:52.016703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 85434bec-fb48-4d8a-be30-e6d696cb41db · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

The Receptive Field as a Regularizer in Deep Convolutional Neural Networks for Acoustic Scene Classification mixup: Beyond Empirical Risk Minimization

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-05-25T10:06:52.013778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

No inbound Pith citation observations are available.