Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T00:30:20.387714Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 0 inbound Pith citation observations for arXiv:2501.18161.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T00:30:20.387714Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
8 of 8 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation ee679cbf-ac27-4127-9505-fd6bf08c765e · outbound
Using Computer Vision for Skin Disease Diagnosis in Bangladesh Enhancing Interpretability and Transparency in Deep Learning Models for Skin Cancer Classification According to this viewpoint, pre-processing is necessary for precise analysis
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation acfdc096-37b7-4c84-9a6d-54f465ce322b · outbound
Using Computer Vision for Skin Disease Diagnosis in Bangladesh Enhancing Interpretability and Transparency in Deep Learning Models for Skin Cancer Classification Section 4 details the materials and procedures
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation f9284383-65b3-43a1-bea6-ca512eb4b02f · outbound
Using Computer Vision for Skin Disease Diagnosis in Bangladesh Enhancing Interpretability and Transparency in Deep Learning Models for Skin Cancer Classification Therefore, all of this noise and artifacting should be eliminated during the pre-processing processes
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 0a010837-f6b0-4936-8003-abadc37c4b3e · outbound
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 01f3e75d-af3c-435e-9c70-1a78becdc369 · outbound
Using Computer Vision for Skin Disease Diagnosis in Bangladesh Enhancing Interpretability and Transparency in Deep Learning Models for Skin Cancer Classification Unresolved cited work
Reference 5
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 5b13337b-02ec-4b5d-bc9c-b057d433783e · outbound
Using Computer Vision for Skin Disease Diagnosis in Bangladesh Enhancing Interpretability and Transparency in Deep Learning Models for Skin Cancer Classification Unresolved cited work
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 62e27ebf-950e-449e-bbb2-3bf703c449bf · outbound
Using Computer Vision for Skin Disease Diagnosis in Bangladesh Enhancing Interpretability and Transparency in Deep Learning Models for Skin Cancer Classification 4 PROPOSED METHODOLOGY In this part, we outline the subsequent phases and our methodology's flowchart, which is seen in Fig
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation c7d4ac07-d9d4-4b20-821f-af38a4088c70 · outbound
Using Computer Vision for Skin Disease Diagnosis in Bangladesh Enhancing Interpretability and Transparency in Deep Learning Models for Skin Cancer Classification Transfer learning with class-weighted and focal loss function for automatic skin cancer classification
Reference 9
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.