Pith. sign in

Paper Citation Record · LEDGER

Detecting and Classifying Defective Products in Images Using YOLO

As of 13 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2412.16935.

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

pith.paper-citation-record.v1
2412.16935 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T06:00:51.793346Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

39 of 39 outbound references displayed

  • verified exact6
  • verified fuzzy21
  • unresolved9
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b7cb2156-a3f3-41a4-a922-2f507765ff08 · outbound

This paper cites Stock market analysis and prediction using LSTM: A case study on technology stocks.

Detecting and Classifying Defective Products in Images Using YOLO Stock market analysis and prediction using LSTM: A case study on technology stocks

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.378753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.650025Z digest=sha256:166a818ac6f50673c05482db9d0da0075895fc08d13655ff4bf1a71bbcdef97b

Observation 1e25a8fb-4777-4260-88d0-13bcffa8509e · outbound

This paper cites Large Language Model (LLM) AI Text Generation Detection based on Transformer Deep Learning Algorithm.

Detecting and Classifying Defective Products in Images Using YOLO Large Language Model (LLM) AI Text Generation Detection based on Transformer Deep Learning Algorithm

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.368941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.654745Z digest=sha256:7d2d38595ccfeb3b221b8750ca8e8291f25ebcf0b3291125973996bd8b51e5b5

Observation f181139a-54fe-40f2-a90f-5f4a78470758 · outbound

This paper cites Automated pneumonia detection in chest x-ray images using deep learning model.

Detecting and Classifying Defective Products in Images Using YOLO Automated pneumonia detection in chest x-ray images using deep learning model

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.358700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.658653Z digest=sha256:2f64a62d8726d315ef8ad5436f636df3c47a59f1c7c16eaeabbca866f305c469

Observation c1a09e39-13cd-47ca-ac4b-ae7133ceca43 · outbound

This paper cites Password complexity prediction based on roberta algorithm.

Detecting and Classifying Defective Products in Images Using YOLO Password complexity prediction based on roberta algorithm

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.348656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.662559Z digest=sha256:6b47c36e81612ef312183dbdeb52930b96795142268c58969e419c86a3c37277

Observation 338ff816-9a74-4b9e-99ed-7de2d46fa054 · outbound

This paper cites A comprehensive evaluation and comparison of enhanced learning methods.

Detecting and Classifying Defective Products in Images Using YOLO A comprehensive evaluation and comparison of enhanced learning methods

Reference 5

Resolution
malformed identifier
raw_fallback, observed 2026-08-11T06:00:52.338427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.666549Z digest=sha256:c4263821e4bc0ac47cb1f159e30c3a0f999a46be4588af5fef05ad9ff3578a92

Observation a2a8ada6-c1e2-4e99-b8c3-c4a1dc13b756 · outbound

This paper cites Spam detection and classification based on distilbert deep learning algorithm.

Detecting and Classifying Defective Products in Images Using YOLO Spam detection and classification based on distilbert deep learning algorithm

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.328552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.670339Z digest=sha256:5c8f983872bac13c478b25eb15ef219e8fcf00a919d8b566d5de1ae640558e43

Observation 22091b65-317b-4014-b64d-3ecee4b7ad27 · outbound

This paper cites Improved YOLOv5 Based on Attention Mechanism and FasterNet for Foreign Object Detection on Railway and Airway tracks.

Detecting and Classifying Defective Products in Images Using YOLO Improved YOLOv5 Based on Attention Mechanism and FasterNet for Foreign Object Detection on Railway and Airway tracks

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-11T06:00:51.674004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T06:00:51.674004Z digest=sha256:f6fe82a6ec96e057042562dbad51203a9ca38a9051a05165e2514861aca02b4b

Observation e047ad81-8a9f-4170-be8b-5e439e0233a6 · outbound

This paper cites Comparative analysis of x-ray image classification of pneumonia based on deep learning algorithm algorithm.

Detecting and Classifying Defective Products in Images Using YOLO Comparative analysis of x-ray image classification of pneumonia based on deep learning algorithm algorithm

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.318099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.677668Z digest=sha256:6cf3f2d5fa3502341ea7fd26ad72f7626dde48dfb429fb31183aed59bac3db48

Observation ca329d80-9980-472f-ac70-3d899f2da0af · outbound

This paper cites A Neural Matrix Decomposition Recommender System Model based on the Multimodal Large Language Model.

Detecting and Classifying Defective Products in Images Using YOLO A Neural Matrix Decomposition Recommender System Model based on the Multimodal Large Language Model

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-11T06:00:51.681334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T06:00:51.681334Z digest=sha256:71472850bdb2ec74bb941cff26eeed258b0b1fd9d283d8c63efc8b86f68da992

Observation 55b6b8bf-15b7-4e51-8787-5f4639b07115 · outbound

This paper cites Transformer-Based Classification Outcome Prediction for Multimodal Stroke Treatment.

Detecting and Classifying Defective Products in Images Using YOLO Transformer-Based Classification Outcome Prediction for Multimodal Stroke Treatment

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-11T06:00:51.685012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T06:00:51.685012Z digest=sha256:45e7dacdc643fff42f9f1d0693ceffceb63609ee01eb36b8193e245f813d416a

Observation 5c40e629-975a-4c7d-ba32-fd6719af1ec8 · outbound

This paper cites A Multimodal Fusion Network For Student Emotion Recognition Based on Transformer and Tensor Product.

Detecting and Classifying Defective Products in Images Using YOLO A Multimodal Fusion Network For Student Emotion Recognition Based on Transformer and Tensor Product

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T06:00:51.688795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T06:00:51.688795Z digest=sha256:bd5640e171019602938bf8ebed93d896a2779709401c2e45656a497060aec1b7

Observation c0b73be6-548d-4d55-89be-011add387b14 · outbound

This paper cites The cloud-based design of unmanned constant temperature food delivery trolley in the context of artificial intelligence.

Detecting and Classifying Defective Products in Images Using YOLO The cloud-based design of unmanned constant temperature food delivery trolley in the context of artificial intelligence

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.306614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.692645Z digest=sha256:f892f6960df2924b3b4687af970dfcfba8950b27acbabee56f185fd4ae29d56b

Observation cc6dad6e-f2c7-4057-82f9-222070489a7c · outbound

This paper cites Make Scale Invariant Feature Transform “Fly.

Detecting and Classifying Defective Products in Images Using YOLO Make Scale Invariant Feature Transform “Fly

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.296370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.696391Z digest=sha256:59659a781567ce7fd0cd4b2419fe0b85eff38ef1d158a55f0c65ddde2fdf397e

Observation 0aa56517-9deb-4a53-9a85-84966a5a802a · outbound

This paper cites Lidar and Monocular Sensor Fusion Depth Estimation.

Detecting and Classifying Defective Products in Images Using YOLO Lidar and Monocular Sensor Fusion Depth Estimation

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.285893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.700079Z digest=sha256:b88959631c2d260459ece69be7d3a3b2a0cc24f40fc9d74be79514f516e26cd6

Observation c3219adc-ba43-4d44-ae12-2c0094a3e3fb · outbound

This paper cites Unraveling large language models: From evolution to ethical implications-introduction to large language models.

Detecting and Classifying Defective Products in Images Using YOLO Unraveling large language models: From evolution to ethical implications-introduction to large language models

Reference 15

Resolution
malformed identifier
raw_fallback, observed 2026-08-11T06:00:52.274878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.704010Z digest=sha256:a33923f6c8b6fcf9b3fad7a87181de987d6269c5ed39d7a3331914c464e85ef1

Observation 349897be-9682-47ec-b1cb-0ea00bb8bc9b · outbound

This paper cites an unresolved cited work.

Detecting and Classifying Defective Products in Images Using YOLO Unresolved cited work

Reference 16

Resolution
verified exact
doi, observed 2026-08-11T06:00:51.838889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.707815Z digest=sha256:1fd4e116d8e728637973cff7efda16cc94eb9bbaac74a2f1182f1c912aa52e1d

Observation 68b28c86-008f-4b67-b618-3f06353253af · outbound

This paper cites Research on Heterogeneous Computation Resource Allocation based on Data-driven Method.

Detecting and Classifying Defective Products in Images Using YOLO Research on Heterogeneous Computation Resource Allocation based on Data-driven Method

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-11T06:00:52.077910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.711718Z digest=sha256:d25dea85e2973a2c564bc7568bc4fd0cee962a8af4e82113fa9e0fc3aa15401c

Observation 53ba10f4-520a-4d3a-be79-162c1b8e14de · outbound

This paper cites Deep Learning Applications in the Medical Image Recognition.

Detecting and Classifying Defective Products in Images Using YOLO Deep Learning Applications in the Medical Image Recognition

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.264868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.715807Z digest=sha256:e13cd7d27357d8e4214fbd98507d9ae8dc76d6768fe6c3e766d64bbebef5f970

Observation 8cc59dd6-d303-4654-b6d0-4665b0e6bc85 · outbound

This paper cites Going Blank Comfortably: Positioning Monocular Head-Worn Displays When They are Inactive.

Detecting and Classifying Defective Products in Images Using YOLO Going Blank Comfortably: Positioning Monocular Head-Worn Displays When They are Inactive

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.254862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.719649Z digest=sha256:66619e33f545713c2f2bea96d43454dd6bf13d6c575d15bfa4ba338578011c00

Observation c8a23d64-f23b-4109-8494-cfd86099409f · outbound

This paper cites Looking From a Different Angle: Placing Head-Worn Displays Near the Nose.

Detecting and Classifying Defective Products in Images Using YOLO Looking From a Different Angle: Placing Head-Worn Displays Near the Nose

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.244514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.723567Z digest=sha256:68229d4a7fc319b85299e937ba2ce2b92b08c26a86a3eb178cc06de67a5c830f

Observation f8a13d3b-0088-4842-8155-282b654cad27 · outbound

This paper cites Twitter Sentiment analysis of covid vaccines[C]//2021 5th International Conference on Artificial Intelligence and Virtual Reality (AIVR).

Detecting and Classifying Defective Products in Images Using YOLO Twitter Sentiment analysis of covid vaccines[C]//2021 5th International Conference on Artificial Intelligence and Virtual Reality (AIVR)

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.233791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.727277Z digest=sha256:b520a2307df1428b224506427f664604549be2eda8847b6f52db7510681669d8

Observation 51d556bf-5234-4ae3-8073-10889fffc9b6 · outbound

This paper cites Artificial intelligence aspect of transportation analysis using large scale systems[C]//Proceedings of the 2023 6th Artificial Intelligence and Cloud Computing Conference.

Detecting and Classifying Defective Products in Images Using YOLO Artificial intelligence aspect of transportation analysis using large scale systems[C]//Proceedings of the 2023 6th Artificial Intelligence and Cloud Computing Conference

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.223214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.730853Z digest=sha256:160b21a2bbd953e83ed7278db93a76b6405df824892b968f88f9a315994c04db

Observation b033791b-e459-4393-9e11-cc7a0c507265 · outbound

This paper cites an unresolved cited work.

Detecting and Classifying Defective Products in Images Using YOLO Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-08-11T06:00:52.212386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.734544Z digest=sha256:5858b2b996ee44babbf54866709e05f79dd73bf75b912aefb13c42b8215ee62f

Observation ab4f57d4-f6a7-4f84-93cd-1ae5dc3db3f5 · outbound

This paper cites an unresolved cited work.

Detecting and Classifying Defective Products in Images Using YOLO Unresolved cited work

Reference 24

Resolution
verified exact
doi, observed 2026-08-11T06:00:51.826564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.738079Z digest=sha256:81bf73a9cea6fd4b1823fe9c038bd344a9c062f8184e75c104a0dd1536f6017f

Observation 82e6225c-9966-4911-95fa-8a44cdf44882 · outbound

This paper cites Predicting 30-Day Hospital Readmission in Medicare Patients: Insights from an LSTM Deep Learning Model.

Detecting and Classifying Defective Products in Images Using YOLO Predicting 30-Day Hospital Readmission in Medicare Patients: Insights from an LSTM Deep Learning Model

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.200775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.741751Z digest=sha256:c12e11715ee8c7e43e8e24676bdac163f70cfc3ba39142151b058ce12e748f03

Observation d6e60381-515a-4fb8-b8de-b8f107d1e2ff · outbound

This paper cites Research on image generation optimization based deep learning.

Detecting and Classifying Defective Products in Images Using YOLO Research on image generation optimization based deep learning

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.189117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.745716Z digest=sha256:64b8b33bff3c730ca7ba1fb148e7bb0f0ec47e622e1ddb54d30595541e8e5f08

Observation 3ccecb54-a933-4d34-ad94-8ceb266506d3 · outbound

This paper cites The application of Augmented Reality (AR) in Remote Work and Education.

Detecting and Classifying Defective Products in Images Using YOLO The application of Augmented Reality (AR) in Remote Work and Education

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T06:00:51.749390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T06:00:51.749390Z digest=sha256:b6f5c639d04fae1f4f2a7be97527fdaa992779308a09eba35eb10e326a798d5d

Observation 418d47a8-b949-4937-a5c6-d666a795018c · outbound

This paper cites Utilizing Deep Learning to Optimize Software Development Processes.

Detecting and Classifying Defective Products in Images Using YOLO Utilizing Deep Learning to Optimize Software Development Processes

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-11T06:00:51.753250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T06:00:51.753250Z digest=sha256:0366a09e425f6d32750fbfcf79bad4438fa694c0240a2b25a2497f02fc836b23

Observation 1a4ce04c-2fc4-45b5-afab-c47d7feb14dd · outbound

This paper cites DRAL: Deep Reinforcement Adaptive Learning for Multi-UAVs Navigation in Unknown Indoor Environment.

Detecting and Classifying Defective Products in Images Using YOLO DRAL: Deep Reinforcement Adaptive Learning for Multi-UAVs Navigation in Unknown Indoor Environment

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-11T06:00:51.758126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T06:00:51.758126Z digest=sha256:aa904894fd7a108353d96d764ea0330921ec4ad613804d23a8ca73b76b730e05

Observation cfc66d2b-7918-4de0-90be-bff82a3ea186 · outbound

This paper cites Robust Domain Generalization for Multi-modal Object Recognition.

Detecting and Classifying Defective Products in Images Using YOLO Robust Domain Generalization for Multi-modal Object Recognition

Reference 30

Resolution
verified exact
local_arxiv, observed 2026-08-11T06:00:52.031769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.761865Z digest=sha256:a55dbbe2d0acc3044cbe867e74c3613db4c8d19b8be5daebfadb2b408876d1b7

Observation 0324f5f5-eaf5-4552-94e0-cb5e7514e54c · outbound

This paper cites Optimizing Automated Picking Systems in Warehouse Robots Using Machine Learning.

Detecting and Classifying Defective Products in Images Using YOLO Optimizing Automated Picking Systems in Warehouse Robots Using Machine Learning

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-11T06:00:51.765637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T06:00:51.765637Z digest=sha256:12693deec42fe6e08adca697af1e541286a330a511635fe8ee3b2fabf6bbbd5a

Observation 5be8e6a3-e044-47cf-92fa-78e99286b402 · outbound

This paper cites Research on adaptive algorithm recommendation system based on parallel data mining platform.

Detecting and Classifying Defective Products in Images Using YOLO Research on adaptive algorithm recommendation system based on parallel data mining platform

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.175895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.769137Z digest=sha256:6e60677e3156535c0b906bc6c4bbba9ba56b576bfe57b947abf0de74e69624d6

Observation 0fdba977-7f27-43e8-9a06-674ce4e7a1b0 · outbound

This paper cites Research on Prediction Recommendation System Based on Improved Markov Model.

Detecting and Classifying Defective Products in Images Using YOLO Research on Prediction Recommendation System Based on Improved Markov Model

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.164777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.772768Z digest=sha256:e265613f6af43d873596c4ca62a1740bb30f58ec676ef080aa49a17b9a73b3e0

Observation 229324e7-1f8f-4a84-bb70-f38de9b2c04e · outbound

This paper cites Advances in Computer, Signals and Systems (2024) Vol.

Detecting and Classifying Defective Products in Images Using YOLO Advances in Computer, Signals and Systems (2024) Vol

Reference 34

Resolution
metadata mismatch
raw_fallback, observed 2026-08-11T06:00:51.961034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.776372Z digest=sha256:56343962e88d9d93f3eb246b47257f2ea7c290d996f10ef63d30ccd4d8275477

Observation b46dfb7a-e7b8-43bc-bd94-e0ccf72c7a34 · outbound

This paper cites Deep Adaptive Interest Network: Personalized Recommendation with Context-Aware Learning.

Detecting and Classifying Defective Products in Images Using YOLO Deep Adaptive Interest Network: Personalized Recommendation with Context-Aware Learning

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-11T06:00:51.874366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.779954Z digest=sha256:c65454634bdbf41bd4b7ca5aa344cd223b11b4b7d8b52cee00692a5cbb991c48

Observation a5ed90dc-1063-4562-945c-70548938d346 · outbound

This paper cites Nonlinear Energy Harvesting with Tools from Machine Learning.

Detecting and Classifying Defective Products in Images Using YOLO Nonlinear Energy Harvesting with Tools from Machine Learning

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.154113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.783510Z digest=sha256:af047f06dec991ae858cc909e54f642feb583946623b5e1af44e956a8584d186

Observation 3a943eee-96b3-4ecf-b784-16c249be0754 · outbound

This paper cites A model-free sampling method for basins of attraction using hybrid active learning (HAL).

Detecting and Classifying Defective Products in Images Using YOLO A model-free sampling method for basins of attraction using hybrid active learning (HAL)

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.143376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.786767Z digest=sha256:c5195632158139b650a5cda726b2d0327c11da754d1e5310b325ebb7bde6bab9

Observation c5df2885-2e0c-4565-b488-fba68bb83324 · outbound

This paper cites Constrained attractor selection using deep reinforcement learning.

Detecting and Classifying Defective Products in Images Using YOLO Constrained attractor selection using deep reinforcement learning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T06:00:52.131469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.790069Z digest=sha256:2b92cfd6950bec286f16ebc177bae9ead5aba7f34d2f711ca82d92e64890fb96

Observation a38e3cdd-4805-4631-9e38-1c71fa671dd5 · outbound

This paper cites Attractor Selection in Nonlinear Energy Harvesting Using Deep Reinforcement Learning.

Detecting and Classifying Defective Products in Images Using YOLO Attractor Selection in Nonlinear Energy Harvesting Using Deep Reinforcement Learning

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-08-11T06:00:51.858348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T06:00:51.793346Z digest=sha256:8f1d66faf72ca36c9ec2c602b404a388d65b77f13b479481248de73b004c6dd2

Pith citing papers

No inbound Pith citation observations are available.