Paper Citation Record · LEDGER

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT

As of 20 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2504.16128.

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

pith.paper-citation-record.v1
2504.16128 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

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One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:01:03.406586Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T12:01:03.494103Z

Reference resolution

52 of 52 outbound references displayed

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External citation measurements

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Outbound references

Observation 117ea906-aa1d-40d8-a3d3-2298631ba10c · outbound

This paper cites A comparative study of fine-tuning deep learning models for plant disease identification,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT A comparative study of fine-tuning deep learning models for plant disease identification,

Reference 1

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Observation cecfe6bb-f305-43b9-9205-6760abb8f353 · outbound

This paper cites Deep learning in agriculture: A survey,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Deep learning in agriculture: A survey,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:19.089235Z

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Observation 002a6220-41dc-4298-94a0-330123350c2b · outbound

This paper cites Brahimi, M.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Brahimi, M

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:19.069028Z

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Observation 6b463c51-0e43-4b0c-824e-931a1f020f22 · outbound

This paper cites Deep learning models for plant disease detection and diagnosis,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Deep learning models for plant disease detection and diagnosis,

Reference 4

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Observation 21802376-9c22-41b4-8b75-b837b98d4a94 · outbound

This paper cites A survey on different plant diseases detection using machine learning techniques,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT A survey on different plant diseases detection using machine learning techniques,

Reference 5

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Observation 94cfc68a-c4a4-430c-bbb8-d52a50f3cbf6 · outbound

This paper cites A review on the main challenges in automatic plant disease identification based on visible range images,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT A review on the main challenges in automatic plant disease identification based on visible range images,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:19.028533Z

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Observation 09a8b0e8-25a1-445c-9014-e4545bd72bbb · outbound

This paper cites Towards sustainable agriculture: A transformer-based hybrid model for advanced leaf disease classification,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Towards sustainable agriculture: A transformer-based hybrid model for advanced leaf disease classification,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:19.015164Z

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Observation 7791501f-030f-4c27-8124-d8a987ad79ea · outbound

This paper cites Comparing vision transformers and convolutional neural networks for image classification: A literature review,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Comparing vision transformers and convolutional neural networks for image classification: A literature review,

Reference 8

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Observation 36b1dd21-7228-4935-9fea-8cd285cdf353 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 9

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Observation b639665f-1255-4713-b448-9e6365caf2bf · outbound

This paper cites Transformers in vision: A survey,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Transformers in vision: A survey,

Reference 10

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Observation 401f3418-19eb-4271-a0c5-e8301cf8d562 · outbound

This paper cites End-to-end object detection with transformers,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT End-to-end object detection with transformers,

Reference 11

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Observation f0ff29e3-3124-4aa9-88ca-7a09be03016e · outbound

This paper cites Image Transformer.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Image Transformer

Reference 12

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Observation b162685f-314a-4256-9299-93941631e62f · outbound

This paper cites Training data-efficient image transformers & distillation through attention,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Training data-efficient image transformers & distillation through attention,

Reference 13

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Observation 535d6647-06df-4dfe-a79c-878af5baa8c8 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 14

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Observation c26e2b7c-d22e-47e9-86d7-392ac6d006c9 · outbound

This paper cites Motion strategies for a cobot in a context of intermittent haptic interface,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Motion strategies for a cobot in a context of intermittent haptic interface,

Reference 15

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Observation 8179d457-2496-468c-923d-d79114d02a16 · outbound

This paper cites Transformer in Transformer.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Transformer in Transformer

Reference 16

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Observation 2e9c7991-a157-41a3-8419-3c33a1eedcd8 · outbound

This paper cites Searching for MobileNetV3 ,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Searching for MobileNetV3 ,

Reference 17

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Observation 1ab757e8-2561-47c2-b231-e73010da02cc · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Distilling the Knowledge in a Neural Network

Reference 18

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Observation 2d7e350a-e6ef-4489-b56f-a008744a6276 · outbound

This paper cites Leveraging logit uncertainty for better knowledge distillation,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Leveraging logit uncertainty for better knowledge distillation,

Reference 19

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Observation af069518-7398-4d44-ad9d-f5d52e08ef7d · outbound

This paper cites Tomato leaf dis- ease recognition based on multi-task distillation learning,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Tomato leaf dis- ease recognition based on multi-task distillation learning,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:18.961941Z

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Observation 66549447-9d21-43a3-89a0-13e25cd6581b · outbound

This paper cites An improved deep learning approach for localization and recognition of plant leaf diseases,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT An improved deep learning approach for localization and recognition of plant leaf diseases,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:18.949764Z

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Observation 28f52386-57a9-4b8b-a8e1-5883ab7d3e4c · outbound

This paper cites Attention Is All You Need.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Attention Is All You Need

Reference 22

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Observation fc816976-4d8e-42c6-b28b-f7821022c3cb · outbound

This paper cites Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer,

Reference 23

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Observation b2b3926c-4787-4f63-a09f-b15b2fa790a8 · outbound

This paper cites Revisiting knowledge distillation via label smoothing regularization,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Revisiting knowledge distillation via label smoothing regularization,

Reference 24

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Observation 219e170f-6f51-41a8-be50-399b2fbd7b0f · outbound

This paper cites Farmbeats: an iot platform for data-driven agriculture,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Farmbeats: an iot platform for data-driven agriculture,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:18.912212Z

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Observation 87f31264-d000-4faa-90e3-73a1ba58c5d8 · outbound

This paper cites An open access repository of images on plant health to enable the development of mobile disease diagnostics,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT An open access repository of images on plant health to enable the development of mobile disease diagnostics,

Reference 26

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Observation 8c2af35f-f2db-4f87-8038-d7cdc90f13fb · outbound

This paper cites Imagenet classification with deep convolutional neural networks,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Imagenet classification with deep convolutional neural networks,

Reference 27

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Observation ff42b590-2ecd-49f2-93db-3dbc3636a3a6 · outbound

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

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 28

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Observation 855bd2dd-f9cf-46b8-b6e0-f2ce7558d4ba · outbound

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Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 29

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Observation 3776e7af-a0d5-4e30-8302-bc54295a2a6a · outbound

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Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Visual Transformers: Token-based Image Representation and Processing for Computer Vision

Reference 30

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This paper cites MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer

Reference 31

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Observation 9089776a-8b97-476a-951b-cb0b6ea6eeb4 · outbound

This paper cites Low-power deep learning model for plant disease detection for smart-hydroponics using knowledge distillation techniques,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Low-power deep learning model for plant disease detection for smart-hydroponics using knowledge distillation techniques,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:18.875326Z

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Observation dde483f8-d4b0-4db4-9394-7f861ce4d652 · outbound

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

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 33

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Observation d88d75c5-d6ae-477a-8010-a7f515882040 · outbound

This paper cites Knowledge distillation from bert transformer to speech transformer for intent classification,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Knowledge distillation from bert transformer to speech transformer for intent classification,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:18.863013Z

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Observation e788d764-2ce7-480a-abc5-6de549304fb0 · outbound

This paper cites Pmvt: a lightweight vision transformer for plant disease identification on mobile devices,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Pmvt: a lightweight vision transformer for plant disease identification on mobile devices,

Reference 35

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Observation b7d5c48f-b244-45f6-a7c4-bb0adb694f9d · outbound

This paper cites Show, Attend and Distill:Knowledge Distillation via Attention-based Feature Matching.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Show, Attend and Distill:Knowledge Distillation via Attention-based Feature Matching

Reference 36

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Observation de07d796-c78b-498c-adc4-e5d61782a433 · outbound

This paper cites Frequency attention for knowledge distillation,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Frequency attention for knowledge distillation,

Reference 37

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Observation da69a99e-1cd1-40fd-87d2-84ae62981ae8 · outbound

This paper cites A gift from knowledge distillation: Fast optimization, network minimization and transfer learning,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT A gift from knowledge distillation: Fast optimization, network minimization and transfer learning,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:18.838809Z

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Observation 694ab0d1-00c9-402f-9885-c830683d4129 · outbound

This paper cites Knowledge Distillation in Vision Transformers: A Critical Review.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Knowledge Distillation in Vision Transformers: A Critical Review

Reference 39

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This paper cites Cross-architecture knowledge distillation,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Cross-architecture knowledge distillation,

Reference 40

Resolution: verified exact; doi, observed 2026-08-16T11:41:18.244610Z

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Observation ac9ec1dd-6b4a-4d60-9f97-c8f17d3b0eec · outbound

This paper cites Vitkd: Feature- based knowledge distillation for vision transformers,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Vitkd: Feature- based knowledge distillation for vision transformers,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:18.825822Z

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Observation 7c848e54-ad90-46d4-8690-a701f2adbbb2 · outbound

This paper cites Internet of things in agriculture, recent advances and future challenges,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Internet of things in agriculture, recent advances and future challenges,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:18.813266Z

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Observation 7aadae2a-6edd-4c89-be42-3d56ef33f7af · outbound

This paper cites Role of iot technology in agriculture: A systematic literature review,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Role of iot technology in agriculture: A systematic literature review,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:18.801246Z

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Observation 5e7a2a0e-4c72-4373-88fe-e307703d7199 · outbound

This paper cites H-at: Hybrid attention transfer for knowledge distillation,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT H-at: Hybrid attention transfer for knowledge distillation,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:18.789301Z

Source-reported events for the cited work

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Observation d022b4cd-cd6b-4325-8379-3a25864c63c5 · outbound

This paper cites “tomato-village.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT “tomato-village

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:18.772910Z

Source-reported events for the cited work

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Observation 20478b19-8497-408b-9b35-53368e4aab0d · outbound

This paper cites Dataset of tomato leaves,.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Dataset of tomato leaves,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:18.760454Z

Source-reported events for the cited work

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Observation 299fc951-c3ba-4104-8c64-7f7f7f36643f · outbound

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

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT EfficientNet: Rethinking model scaling for convolutional neural networks,

Reference 47

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Source-reported events for the cited work

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This paper cites Tiny machine learning: Progress and futures [feature],.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Tiny machine learning: Progress and futures [feature],

Reference 49

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Source-reported events for the cited work

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Observation 54999ac5-4ac4-4ae6-a5eb-8553ab55e9a8 · outbound

This paper cites An open access repository of images on plant health to enable the development of mobile disease diagnostics.

Reference 2016

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Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT MobileNetV2: Inverted Residuals and Linear Bottlenecks

Reference 2018

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This paper cites Since 2024, he works at Soroti university as a lecturer.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Since 2024, he works at Soroti university as a lecturer

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:18.740313Z

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 8fc43bd6-f222-4b72-886e-3d124d90dfde · outbound

This paper cites Available: https://doi.org/10.1007/s00530-023-01158-y.

Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT Available: https://doi.org/10.1007/s00530-023-01158-y

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-16T11:41:18.162851Z

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Pith citing papers

Observation e8e6c4b5-6073-46b6-9c6d-8e81a67f4aa3 · inbound

Vision-Based Embedded System for Noncontact Monitoring of Preterm Infant Behavior in Low-Resource Care Settings cites this paper.

Vision-Based Embedded System for Noncontact Monitoring of Preterm Infant Behavior in Low-Resource Care Settings Hybrid Knowledge Transfer through Attention and Logit Distillation for On-Device Vision Systems in Agricultural IoT

Reference 31

Resolution: metadata mismatch; local_arxiv, observed 2026-08-05T12:01:03.498444Z

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