Pith. sign in

Paper Citation Record · LEDGER

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis

As of 15 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2501.12023.

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

pith.paper-citation-record.v1
2501.12023 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:39:15.213680Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

50 of 50 outbound references displayed

  • verified exact0
  • verified fuzzy18
  • unresolved32
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 95ee433f-586a-4b9b-9b10-da07dcfd4138 · outbound

This paper cites Diagnosis and complications of cushing’s syndrome: a consensus state- ment,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Diagnosis and complications of cushing’s syndrome: a consensus state- ment,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.842441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.009674Z digest=sha256:609c811ca59366c70fb0b12d51a48b9fd6a30a0ded6ecd3fe86dce7fdef9c7f5

Observation 17c002c6-6a27-472a-aa5b-b07b7e4092c5 · outbound

This paper cites Persistence of myopathy in cushing’s syndrome: evaluation of the german cushing’s registry,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Persistence of myopathy in cushing’s syndrome: evaluation of the german cushing’s registry,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.828420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.015218Z digest=sha256:c72d2eb9039e04c21a27c0db8a6b0bfd8dafd5a40e0e9892fbaba742cd3eb6ea

Observation e99d15c0-8d15-4bfc-af31-69e292e55fc3 · outbound

This paper cites Demographic factors and the presence of comorbidities do not promote early detection of cushing’s disease and acromegaly,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Demographic factors and the presence of comorbidities do not promote early detection of cushing’s disease and acromegaly,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.814723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.020410Z digest=sha256:dfb564c1115f5388201907b97d6672f645695058bb53481d4c42cf539b03f787

Observation 19ff71af-27d7-4e11-8d1b-8706fb4508bb · outbound

This paper cites Computer vision technology in the differential diagnosis of cushing’s syndrome,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Computer vision technology in the differential diagnosis of cushing’s syndrome,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.800186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.024471Z digest=sha256:e2281210ea0b401fc468556221b7f76d8e666613f4ae2bcc68aea36a20c08319

Observation d45c6a18-279f-48e4-89dc-a242eb3ab661 · outbound

This paper cites Deep-learning approach to automatic identifi- cation of facial anomalies in endocrine disorders,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Deep-learning approach to automatic identifi- cation of facial anomalies in endocrine disorders,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.786336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.028690Z digest=sha256:4fa4f5f3c784b39747faf246b54e524f078aae93dd862bab842ad8196b0b7958

Observation addcb87e-8bdb-4e48-b850-b8c5a01253ba · outbound

This paper cites Dlib-ml: A machine learning toolkit,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Dlib-ml: A machine learning toolkit,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.772657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.033181Z digest=sha256:c2f714f18b239f66a32ea6257e2b16fbf1000c0a2cb38824a5742b5fef4eb07e

Observation 30776f60-8467-4c9f-9d3a-75b63ec5ae55 · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Imagenet: A large-scale hierarchical image database,

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.037587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.037587Z digest=sha256:4ee2d8dc5864daa8e153ce41d8fa7d19b33a10dbf90a305d75d27146f258621d

Observation 2bc31c68-11f5-4f5d-bcca-2f960e9a0b8c · outbound

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

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.041701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.041701Z digest=sha256:df0eff30ad894c4d8025b4c7251009e3615452b4f0f12708fb2460be81368c77

Observation 9172ef4e-c09b-4557-9c72-b03e109f4988 · outbound

This paper cites Attention is all you need,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Attention is all you need,

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.047338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.047338Z digest=sha256:478eb744b56d5c0568336b53cc4d909951e497fd52748602af0af7fc17da2d0d

Observation 95a46b8e-6ebe-4865-b245-8673f5681462 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.051602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.051602Z digest=sha256:e3d053b3de8a9b1df9ec8ba787569fb794b98f52460f2223f0abb906fb4f6531

Observation 7f78b556-b4d7-476a-bd22-6b8993a9cc7c · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.055934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.055934Z digest=sha256:b3450e3b86d8fdff137ac82daaa62d9d0897151c2190cc2a7da3f7addb8175f6

Observation a914d0b6-c288-4d68-aa4a-0a44387cc6a1 · outbound

This paper cites Improving language understanding by generative pre- training,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Improving language understanding by generative pre- training,

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.060012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.060012Z digest=sha256:4627395341ce988a864fcc02da97c3e55da733279a07197252189af0af522bc7

Observation 7932f0c3-8ee8-44eb-8448-1eb1a94607ef · outbound

This paper cites Language models are unsupervised multitask learners,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Language models are unsupervised multitask learners,

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.063274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.063274Z digest=sha256:d7dc729c5a464c8c4a8250e8b621cfec5683d558f3018f35ed40b4631beff2a3

Observation ae4a87ca-a05a-4ea2-ae7a-5eafbc7ecb56 · outbound

This paper cites Language Models are Few-Shot Learners.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Language Models are Few-Shot Learners

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.067641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.067641Z digest=sha256:887f20667592071b225224e492f3bf09f24f0cb9c97a48e64306178249f98031

Observation 6a8eba97-0e16-48d1-b1cc-53ab742fedb7 · outbound

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

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.721939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.075036Z digest=sha256:253b05849835b7e53a9f356890f51bb9150d5b00816dcf8d8623323eed9485a7

Observation 40055d3e-6f8b-4d8a-a9b8-a5ec164642ab · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis DINOv2: Learning Robust Visual Features without Supervision

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.078829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.078829Z digest=sha256:1c56e18b9c8e309550b9130a5750a49a8644f1a0d41ee878b901ad424b83abdf

Observation babf691d-d795-47a5-bc3b-a134260a9b8d · outbound

This paper cites Segment anything,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Segment anything,

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.084598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.084598Z digest=sha256:1e65c29896690f30ca92115932a51c36926197027f19bea6adfd2613973db341

Observation aaf82f85-79f3-410a-ae80-e57b76de792c · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis SAM 2: Segment Anything in Images and Videos

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.089598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.089598Z digest=sha256:83a3c11eff80b3bf2ca04ed45108106c8a28e29045e6110e1e73eaa589d1bbda

Observation 33140236-8fd2-4c62-9e8b-ff1bffdeb313 · outbound

This paper cites Segment anything in medical images,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Segment anything in medical images,

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.094771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.094771Z digest=sha256:efd55e3140e51dc9eb8a17d7ab156dd2895764c7d5028fd88dc1fa7b9b51518e

Observation 35533c5d-9ae9-4f59-b9bf-a020cbee3710 · outbound

This paper cites Are natural domain foundation models useful for medical image classification?.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Are natural domain foundation models useful for medical image classification?

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.689639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.099636Z digest=sha256:346a81a962667b7ff346f5a7001eb2da22ee6e285529748b6541c89c6c8b455f

Observation d0759c8b-1479-4f14-9a39-9741e75978fd · outbound

This paper cites Densely connected convolutional networks,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Densely connected convolutional networks,

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.104217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.104217Z digest=sha256:8f21eb135e850d244c4ee66ea61dc50222030bd667536cf8d570240f12bbd54f

Observation 35f6980a-ce6f-4d31-ba30-2b7b433060a7 · outbound

This paper cites Deep residual learning for image recognition,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Deep residual learning for image recognition,

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.108782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.108782Z digest=sha256:05fd7f70faf58bf0c761057a850b169e2af82a6fe9027f5812fe1daa1a4cc627

Observation 5d8fb710-ef99-4be0-a52b-22fde9e512be · outbound

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

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.112956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.112956Z digest=sha256:992a97589bac97a0b0ec6805e71e69fcd9cd33cf5d75141fd5b925235ad21203

Observation 38a188f6-99b8-4756-91a5-4d7e6148f156 · outbound

This paper cites Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.116868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.116868Z digest=sha256:13f1145fe0d4359393fd1f41f84aa17bc2e1890e9f53b5c538a3e4f6d50992ba

Observation de1befbd-76c3-4403-8ddd-965fefe1a565 · outbound

This paper cites Ma-sam: Modality-agnostic sam adaptation for 3d medical image segmentation,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Ma-sam: Modality-agnostic sam adaptation for 3d medical image segmentation,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.652047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.120599Z digest=sha256:4cae5f9dabeeb5fe6a1ae252bb3462f2368b068bf1888ff13acf2ee7d85a14ec

Observation bfc083e7-8e97-4f5b-907a-cc3b3c6137ee · outbound

This paper cites SAM-Med2D.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis SAM-Med2D

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.124296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.124296Z digest=sha256:50f10ae74243e505a3bc949eca087b50a95d583b2c10ec95002dd3e86268286c

Observation 6e38f8ff-9757-4534-a690-150ccb448539 · outbound

This paper cites Input augmentation with sam: Boosting medical image segmentation with seg- mentation foundation model,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Input augmentation with sam: Boosting medical image segmentation with seg- mentation foundation model,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.638989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.129008Z digest=sha256:40e41c5d507da50d44b2a0f253965f71f0d8aed7f9b4a46f4fa33a0fbcf0f0a5

Observation 9ec821b7-8613-4cc5-b343-d1e9330f7841 · outbound

This paper cites VIS-MAE: An Efficient Self-supervised Learning Approach on Medical Image Segmentation and Classification.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis VIS-MAE: An Efficient Self-supervised Learning Approach on Medical Image Segmentation and Classification

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.137191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.137191Z digest=sha256:41d3614454d4aa4fadf2ffbd5858b38ff394e7dabf6d66a646579b4c9860f11a

Observation ef10c205-444b-40ce-ab8e-2621e9488823 · outbound

This paper cites Evaluating General Purpose Vision Foundation Models for Medical Image Analysis: An Experimental Study of DINOv2 on Radiology Benchmarks.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Evaluating General Purpose Vision Foundation Models for Medical Image Analysis: An Experimental Study of DINOv2 on Radiology Benchmarks

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.141038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.141038Z digest=sha256:6262e1622829f65fa6619870951041698217d123c002cf8227536a38d0363e65

Observation 02e82cd0-61e4-4d55-af69-f9c817a4f782 · outbound

This paper cites Parameter-efficient fine-tuning of dinov2 vision transformers for lung nodule classification,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Parameter-efficient fine-tuning of dinov2 vision transformers for lung nodule classification,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.624598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.144995Z digest=sha256:fda874f9fa3f707a2018ae26328337e022c6a38c477f4116b0fcd5fad480ab5c

Observation 7a7474a8-9dfc-41f5-a964-30d7f39cf6a7 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis LoRA: Low-Rank Adaptation of Large Language Models

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.148590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.148590Z digest=sha256:ce51d1150e8c926b00f00ff7979c933013e79750a5975bc56f96358ab88427b1

Observation c66307cc-6d36-402a-bf51-f09cc6babc8a · outbound

This paper cites Segment everything everywhere all at once,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Segment everything everywhere all at once,

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.151947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.151947Z digest=sha256:a324cda18154c2b7e93d5b4f0c52b6c1e1ef4fafde4fc64aa7b4f3f6db24555f

Observation 0679d4fb-f974-41e5-9b0f-9cd8918fbb03 · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.155046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.155046Z digest=sha256:2faf806c503a44826d85c5cd11bbcfcd6df3ac4d194ccd16d0fb4ff3bcb5700d

Observation c9d8d95b-e6f1-44b4-aaf4-2d64f2c5381d · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Learning transferable visual models from natural language supervision,

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.158140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.158140Z digest=sha256:7fa3ea8c526f68fe133286ea1b459238415fbe6cc439bb712e809e386ff7acca

Observation e3a4bf29-f69f-4233-a7e6-65f1c37aa415 · outbound

This paper cites Electronic medical records as input to predict postoperative immediate remission of cushing’s disease: application of word embedding,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Electronic medical records as input to predict postoperative immediate remission of cushing’s disease: application of word embedding,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.574002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.161834Z digest=sha256:9f1f99c4c4f48a9f6fac3dce181011800a66b466f8c46c66ce6ff830e9f5e918

Observation 43c9d6f2-f034-4528-843e-e39682cad590 · outbound

This paper cites Learning repre- sentations by back-propagating errors,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Learning repre- sentations by back-propagating errors,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.164898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.164898Z digest=sha256:e16b2e7bf0f4fd236a64e89f240fcbd11c67fae1c09081caa7d8ee76f0cb50df

Observation 4b3dd5a7-9374-44fd-b9ac-55b8781b7806 · outbound

This paper cites Support-vector networks,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Support-vector networks,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.168012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.168012Z digest=sha256:514bb76198c31ce8c522a9561f896afc2c22e205f0b9d2ea806700367ed8652b

Observation 3ddc1862-dc17-41fa-9d6b-25808d0b7809 · outbound

This paper cites Random forests,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Random forests,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.171695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.171695Z digest=sha256:255d2ba2688cbe0bd78061147abbfc43766302212f60d17462d9084341e6e590

Observation 51b35f6d-aa1b-4f63-bff0-879629d6c028 · outbound

This paper cites The regression analysis of binary sequences,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis The regression analysis of binary sequences,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.175204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.175204Z digest=sha256:6129389b0b5e626cedfcfa9c3318023bf1ae735347d31b6da2e384d9ddd6b2fa

Observation 591f12b7-4398-4cfa-a497-f79c7dc1a165 · outbound

This paper cites Toward better prediction of recurrence for cushing’s disease: a factorization-machine based neural approach,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Toward better prediction of recurrence for cushing’s disease: a factorization-machine based neural approach,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.522022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.178889Z digest=sha256:9793ff95d98d9c082173587e8a7f89a300b6db5d538569ddd5bd72d60aa7d18f

Observation 98987f2e-5a89-47e6-a201-7316e79aeba8 · outbound

This paper cites Greedy function approximation: a gradient boosting machine,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Greedy function approximation: a gradient boosting machine,

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.182447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.182447Z digest=sha256:32d61da8b2572ea6f13a35b0521ec4f73d84d29e672b47109e6c176d33ac3345

Observation f980f53e-8eb4-4557-9425-8abdc9752684 · outbound

This paper cites A decision-theoretic generalization of on-line learning and an application to boosting,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis A decision-theoretic generalization of on-line learning and an application to boosting,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.495875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.186120Z digest=sha256:200024c3f5fe8d28a49430dbf6ecf6f53a9edb57cc029fd9abd683abc721c9c1

Observation 941d233b-61b3-4eca-8a89-aa4f1a8aefd9 · outbound

This paper cites Xgboost: A scalable tree boosting system,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Xgboost: A scalable tree boosting system,

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.190073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.190073Z digest=sha256:2f0fac75f899530d4e7e85a33caf863cafb54e162d03e3262839efdefe2aea97

Observation 1e9f7ceb-a68b-4c80-a2ff-6b2fe2e0ecd1 · outbound

This paper cites Machine learn- ing models for classification of cushing’s syndrome using retrospective data,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Machine learn- ing models for classification of cushing’s syndrome using retrospective data,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.472518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.193745Z digest=sha256:a52b2bbceefc3da20fda1ca2c40c9bde2f7e0b2c3f5be35d399178524868a887

Observation 88e86cf6-ce9e-4c4f-8bff-70856d5aa763 · outbound

This paper cites An introduction to kernel and nearest-neighbor non- parametric regression,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis An introduction to kernel and nearest-neighbor non- parametric regression,

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.197369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.197369Z digest=sha256:f6309864c2b69dcc69c8c3013b00ac70b6de1f748e1c0e88d41aff48f05a3cbb

Observation 82a7d273-b820-4151-8bc2-0e0cff889f6a · outbound

This paper cites Principal component analysis-a tutorial,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Principal component analysis-a tutorial,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.451567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.200506Z digest=sha256:dbc8de43dbd0f40ab0a3c2c6866b7a1c9801cfa9a4a0dc051de3d31afe4b1775

Observation ed359e93-e9ea-40b7-88b5-eaa5929d1edd · outbound

This paper cites Classification and regression trees,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Classification and regression trees,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.437977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.203825Z digest=sha256:0eb563a1e4b41f0634b63973abef0629447ee1f65c038f6a8828d398186c73f1

Observation e3f47f08-701f-482e-9f28-ea80cbff723f · outbound

This paper cites Automatic face classification of cushing’s syndrome in women–a novel screening approach,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Automatic face classification of cushing’s syndrome in women–a novel screening approach,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:39:15.418545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-10T17:39:15.207407Z digest=sha256:0e88b16d27cb8535cdf370a30a3f1a55740b75298f58c4836a6ec8e702efead8

Observation 4fd9c5a6-e04a-4b03-9b55-7d2baa560533 · outbound

This paper cites Large-scale machine learning with stochastic gradient de- scent,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Large-scale machine learning with stochastic gradient de- scent,

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.210541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.210541Z digest=sha256:c85be8d90c4ac06b762b7d1e41c7f49a56a3798b3d75ab3cd5a9eac5d485f760

Observation e80d2ebf-e23c-4ff8-bf15-1c9a47996047 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Comparative Analysis of Pre-trained Deep Learning Models and DINOv2 for Cushing's Syndrome Diagnosis in Facial Analysis Pytorch: An imperative style, high-performance deep learning library,

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-10T17:39:15.213680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:39:15.213680Z digest=sha256:8909d77d43b917e0af1a98eb26eafc10e3e50f41a47a2174bc70d3bdfbaaba78

Pith citing papers

No inbound Pith citation observations are available.