Paper Citation Record · LEDGER

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems

As of 8 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2508.20232.

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

pith.paper-citation-record.v1
2508.20232 v1

Coverage vector

measured 39 of 39 reference resolution

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measured 39 of 39 standing notices

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Pith citing papers itemized under the disclosed page cap.

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Source: cited_works

Reference resolution

39 of 39 outbound references displayed

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External citation measurements

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Outbound references

Observation 5e6ca0f1-8b0f-4a66-b3dd-96a62f2ec703 · outbound

This paper cites Variational Information Distillation for Knowledge Transfer.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Variational Information Distillation for Knowledge Transfer

Reference 1

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Observation 3b589048-fb43-4e81-a80e-a45e7a2a41b8 · outbound

This paper cites Plant disease identification from individ- ual lesions and spots using deep learning.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Plant disease identification from individ- ual lesions and spots using deep learning

Reference 2

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Observation f6798768-bc5c-4246-867b-b607d89e7bc3 · outbound

This paper cites Learning Efficient Object Detection Models with Knowledge Distillation, in: Advances in Neural Information Processing Systems, Curran Asso- ciates, Inc.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Learning Efficient Object Detection Models with Knowledge Distillation, in: Advances in Neural Information Processing Systems, Curran Asso- ciates, Inc

Reference 3

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This paper cites Improved Regularization of Convolutional Neural Networks with Cutout.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Improved Regularization of Convolutional Neural Networks with Cutout

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This paper cites Enhancing the Performance of YOLOv9t Through a Knowledge Distillation Approach for Real-Time Detec- tion of Bloomed Damask Roses in the Field.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Enhancing the Performance of YOLOv9t Through a Knowledge Distillation Approach for Real-Time Detec- tion of Bloomed Damask Roses in the Field

Reference 5

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Observation 00aad911-e6e9-4fd0-baba-e0e553ada31c · outbound

This paper cites A Robust Deep-Learning- Based Detector for Real-Time Tomato Plant Diseases and Pests Recogni- tion.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems A Robust Deep-Learning- Based Detector for Real-Time Tomato Plant Diseases and Pests Recogni- tion

Reference 6

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Observation e11a5589-ba4f-4550-aa1a-e526a46ddde3 · outbound

This paper cites Identification of plant leaf diseases using a nine- layer deep convolutional neural network.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Identification of plant leaf diseases using a nine- layer deep convolutional neural network

Reference 7

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Observation 0c400665-08b0-468a-b25f-a6616b3dfcbb · outbound

This paper cites Knowledge Distilla- tion: A Survey.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Knowledge Distilla- tion: A Survey

Reference 8

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Observation c76c1e12-9a8e-461b-b66c-a07f4a4a80b1 · outbound

This paper cites On Calibration of Modern Neural Networks.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems On Calibration of Modern Neural Networks

Reference 9

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Observation 6c03f112-2db9-40d7-8cae-576035b5a914 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Distilling the Knowledge in a Neural Network

Reference 10

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Observation ae7707e2-561e-4296-b4e2-12661f17c1dd · outbound

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

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 11

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Observation cbb0ab1d-c557-49f7-a677-45df74eebfc2 · outbound

This paper cites Like What You Like: Knowledge Distill via Neuron Selectivity Transfer.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Like What You Like: Knowledge Distill via Neuron Selectivity Transfer

Reference 12

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Observation 8532cdbf-44b1-4ee9-b5b2-97b9f75283d1 · outbound

This paper cites A gradual approach to knowledge distillation in deep supervised hashing for large-scale image retrieval.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems A gradual approach to knowledge distillation in deep supervised hashing for large-scale image retrieval

Reference 13

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Observation b97ffa31-0a2d-48e5-9401-cc8dd8e2e235 · outbound

This paper cites A review of the use of convolutional neural networks in agriculture | The Journal of Agri- cultural Science.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems A review of the use of convolutional neural networks in agriculture | The Journal of Agri- cultural Science

Reference 14

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Observation 86bda1a1-57bf-4c86-807f-5d6ba06439b3 · outbound

This paper cites Deep learning in agri- culture: A survey.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Deep learning in agri- culture: A survey

Reference 15

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Observation b37991fe-bc03-4240-bbf4-1f306a8a44fc · outbound

This paper cites Ma- chine Learning in Agriculture: A Review.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Ma- chine Learning in Agriculture: A Review

Reference 16

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Observation 14a9bfcd-5f2b-4a99-81af-7d16a96dce1e · outbound

This paper cites Frontiers | Using Deep Learning for Image-Based Plant Disease Detection URL: https://www.frontiersin.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Frontiers | Using Deep Learning for Image-Based Plant Disease Detection URL: https://www.frontiersin

Reference 17

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Observation 81985cd0-73e7-4e56-827d-9ea735423ca3 · outbound

This paper cites Relational Knowledge Distillation, in: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Relational Knowledge Distillation, in: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp

Reference 18

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Observation 9d0dc177-5ee8-4b37-9a93-fbc42b1388be · outbound

This paper cites Learning Deep Representations with Probabilistic Knowledge Transfer.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Learning Deep Representations with Probabilistic Knowledge Transfer

Reference 19

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Observation 1bb79005-5438-4519-bbd4-6e1419f9f7ef · outbound

This paper cites Computer vision and artificial intel- ligence in precision agriculture for grain crops: A systematic review.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Computer vision and artificial intel- ligence in precision agriculture for grain crops: A systematic review

Reference 20

Resolution: verified exact; doi, observed 2026-08-05T15:17:52.584537Z

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Observation 55ba77ce-5f65-4bd9-b4b6-75bbf4c7dd4f · outbound

This paper cites Correlation Congruence for Knowledge Distillation.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Correlation Congruence for Knowledge Distillation

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-05T15:17:52.574994Z

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Observation 7b4d54ff-ffae-4b93-b7a9-91bb7e7b6d87 · outbound

This paper cites FitNets: Hints for Thin Deep Nets.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems FitNets: Hints for Thin Deep Nets

Reference 22

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Observation 171d1115-c914-42b3-9048-2121d89c24d1 · outbound

This paper cites Plant Disease Detection and Classification by Deep Learning.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Plant Disease Detection and Classification by Deep Learning

Reference 23

Resolution: verified exact; doi, observed 2026-08-05T15:17:52.555590Z

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Observation 9e1d371b-4be5-4df4-88b6-11282916872b · outbound

This paper cites Mo- bileNetV2: Inverted Residuals and Linear Bottlenecks, in: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Mo- bileNetV2: Inverted Residuals and Linear Bottlenecks, in: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 24

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Observation 3133434e-2113-4425-a28b-f61e71e73b67 · outbound

This paper cites Machine Learning Applications for Precision Agriculture: A Comprehensive Review.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Machine Learning Applications for Precision Agriculture: A Comprehensive Review

Reference 25

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This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 26

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This paper cites Contrastive Representation Distillation.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Contrastive Representation Distillation

Reference 27

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Observation 67b2a657-449a-4931-b7fa-e979928743ae · outbound

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ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Similarity-Preserving Knowledge Distillation

Reference 28

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Observation 76cffd1a-b4fd-4d69-b8ab-435b0a4f9357 · outbound

This paper cites Knowledge Distillation and Student-Teacher Learning for Visual Intelligence: A Review and New Outlooks.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Knowledge Distillation and Student-Teacher Learning for Visual Intelligence: A Review and New Outlooks

Reference 29

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Observation 1383c7be-098e-494d-b386-420219e27e42 · outbound

This paper cites Self-training with Noisy Student improves ImageNet classification.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Self-training with Noisy Student improves ImageNet classification

Reference 30

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Observation e123393a-d906-4c7e-89cd-db34c7dccee7 · outbound

This paper cites Knowledge Distillation Meets Self-supervision.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Knowledge Distillation Meets Self-supervision

Reference 31

Resolution: verified exact; doi, observed 2026-08-05T15:17:52.508874Z

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Observation 7014e8ac-22a2-4ea3-812b-6fe3c46766fd · outbound

This paper cites Knowledge Distillation in Generations: More Tolerant Teachers Educate Better Students.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Knowledge Distillation in Generations: More Tolerant Teachers Educate Better Students

Reference 32

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Observation 5ca763e5-2b43-48bd-a062-ba522dd0a44c · outbound

This paper cites CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Features, in: 2019 IEEE/CVF International Conference on Computer Vision (ICCV), pp.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Features, in: 2019 IEEE/CVF International Conference on Computer Vision (ICCV), pp

Reference 33

Resolution: verified exact; raw_fallback, observed 2026-08-05T15:17:52.762973Z

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Observation a4a27fd5-1f0b-4ab4-a8e5-ba334bd75b30 · outbound

This paper cites Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer

Reference 34

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Observation 653c67b2-0ef9-417a-b889-c6ab29a20748 · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems mixup: Beyond Empirical Risk Minimization

Reference 35

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ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Decoupled Knowledge Distillation

Reference 36

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Observation f3d50752-b88c-4de0-9e17-fdc78485cdfd · outbound

This paper cites CropDeep: The Crop Vision Dataset for Deep-Learning-Based Classification and Detection in Precision Agriculture.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems CropDeep: The Crop Vision Dataset for Deep-Learning-Based Classification and Detection in Precision Agriculture

Reference 37

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Observation 3a6ed0d6-cee8-4abd-83b4-3977fb98a6b7 · outbound

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ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems Random Erasing Data Augmentation

Reference 38

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Observation 53076dbf-2c15-4a39-b4de-a4be01d12bad · outbound

This paper cites 1109/CVPR.2018.00474.

ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems 1109/CVPR.2018.00474

Reference 4520

Resolution: verified exact; raw_fallback, observed 2026-08-05T15:17:52.910608Z

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