Paper Citation Record · LEDGER

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification

As of 19 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2509.03754.

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

pith.paper-citation-record.v1
2509.03754 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T10:45:34.534394Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

25 of 25 outbound references displayed

verified exact1
verified fuzzy16
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 26a76664-71cc-4f22-84fa-4409e1831f52 · outbound

This paper cites Ccmt-9: A public dataset for crop classification and disease detection in cashew, cassava, maize, and tomato.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Ccmt-9: A public dataset for crop classification and disease detection in cashew, cassava, maize, and tomato

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.763574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2c58d58f-9842-4608-a112-e4dfe3ea4a9b · outbound

This paper cites High-performance large-scale image recognition without normalization.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification High-performance large-scale image recognition without normalization

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.755644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3b531e37-5cf5-4dd5-a926-d565ef7a09a3 · outbound

This paper cites Neural architecture search on a budget: Taming the complexity of one-shot nas.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Neural architecture search on a budget: Taming the complexity of one-shot nas

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.747396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 36d4dd07-0ba2-40dd-8b65-fb5a35930550 · outbound

This paper cites A Novel Convolutional Neural Network Architecture with a Continuous Symmetry.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification A Novel Convolutional Neural Network Architecture with a Continuous Symmetry

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-05T10:45:34.632169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c440207a-0194-4f12-8eeb-b7f4bd27cd41 · outbound

This paper cites Randaugment: Practical automated data augmentation with a reduced search space.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Randaugment: Practical automated data augmentation with a reduced search space

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.739564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9fa51222-0408-4958-9ac1-1d4d335702a4 · outbound

This paper cites Searching for mobilenetv3.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Searching for mobilenetv3

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.731374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 68862d5b-ac7f-4db0-8265-13e385c43994 · outbound

This paper cites Squeeze-and-excitation networks.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Squeeze-and-excitation networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.723431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e372a164-de8d-458d-addd-c53426539a9c · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T10:45:34.487480Z

Source-reported events for the cited work

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Observation 7bce5878-a9fa-4c9a-a7e2-199fab9fa476 · outbound

This paper cites Deep residual learning for image recognition.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Deep residual learning for image recognition

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.715821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d36581fc-13ef-47f7-9bcd-429f36e7a500 · outbound

This paper cites Unsupervised texture segmentation using gabor filters.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Unsupervised texture segmentation using gabor filters

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.707456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 90c8e061-15d3-4bef-908c-447a53dd8781 · outbound

This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T10:45:34.497655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8292cd7f-f5f5-4d2d-ad3f-be1fd44097ab · outbound

This paper cites Decoupled Weight Decay Regularization.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Decoupled Weight Decay Regularization

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T10:45:34.500529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c2abefb-4ca6-4ff2-b5a6-b2fcc2308875 · outbound

This paper cites DARTS: Differentiable Architecture Search.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification DARTS: Differentiable Architecture Search

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T10:45:34.503184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76bb2333-9b9f-4f27-97c4-4b6a0fbe4ff4 · outbound

This paper cites MobileNetV4 -- Universal Models for the Mobile Ecosystem.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification MobileNetV4 -- Universal Models for the Mobile Ecosystem

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T10:45:34.506261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 775325da-0e0b-479c-acaf-ec9d3250726d · outbound

This paper cites Large-scale evolution of image classifiers.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Large-scale evolution of image classifiers

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.699413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2e308da2-07f6-43d4-977d-a106365b8c0e · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.691324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 57506695-2068-43aa-a62a-fdffe1702b86 · outbound

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

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T10:45:34.513873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4467382c-c0ac-4ad1-bbe8-850f1b29776a · outbound

This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Efficientnet: Rethinking model scaling for convolutional neural networks

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.683264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8ab8ffc7-037e-4c75-b970-17e29e13f10d · outbound

This paper cites Cbam: Convolutional block attention module.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Cbam: Convolutional block attention module

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.674612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 28f53634-4bae-4aea-8409-cfe3eb918252 · outbound

This paper cites Eca-net: Efficient channel attention for deep convolutional neural networks.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Eca-net: Efficient channel attention for deep convolutional neural networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.666095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cc18ddce-4fda-4bc8-ba46-c4857024c23b · outbound

This paper cites An almost complete $t$-intersection theorem for permutations.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification An almost complete $t$-intersection theorem for permutations

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T10:45:34.524264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 296e27d4-40e7-4507-9352-6102299958fd · outbound

This paper cites Neural Architecture Search with Reinforcement Learning.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Neural Architecture Search with Reinforcement Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T10:45:34.526910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da42ba6d-b859-4db8-8c28-958ccc41dd4d · outbound

This paper cites Diversified visual attention networks for fine-grained object classification.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Diversified visual attention networks for fine-grained object classification

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.657838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation effca508-617d-485e-a0d8-91a3fd9735dc · outbound

This paper cites Random erasing data augmentation.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Random erasing data augmentation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.649594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1d5684c3-c7f5-4691-ae33-50d13b8766a7 · outbound

This paper cites Shufflenet: An extremely efficient convolutional neural network for mobile devices.

STA-Net: A Decoupled Shape and Texture Attention Network for Lightweight Plant Disease Classification Shufflenet: An extremely efficient convolutional neural network for mobile devices

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:45:34.641125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.