Home › Entities › academia › CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

Research article (2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018) · cited 1,634× · AI/ML
academia openalex:W2964209782
Press Enter · cited answer in seconds

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

Summary

CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes is a scholarly article[1].

Key Facts

  • CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes's instance of is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes. Retrieved May 24, 2026, from https://4ort.xyz/entity/csrnet-dilated-convolutional-neural-networks-for-understanding-the-highly-congested-scenes
MLA “CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/csrnet-dilated-convolutional-neural-networks-for-understanding-the-highly-congested-scenes.
BibTeX @misc{4ortxyz_csrnet-dilated-convolutional-neural-networks-for-understanding-the-highly-congested-scenes_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes}}, year = {2026}, url = {https://4ort.xyz/entity/csrnet-dilated-convolutional-neural-networks-for-understanding-the-highly-congested-scenes}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes — https://4ort.xyz/entity/csrnet-dilated-convolutional-neural-networks-for-understanding-the-highly-congested-scenes (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/csrnet-dilated-convolutional-neural-networks-for-understanding-the-highly-congested-scenes · Last refreshed: