Researcher Evidence Record
Ikboljon Sobirov
This bounded record lists 13 Pith paper rows and 0 imported work rows attributed to this corpus identity. The enumerated, non-disputed paper rows include eess.IV, cs.AI, cs.CV work dated 2022 to 2024. The record describes sources and coverage; it makes no judgment about the person.
Compiled coverage vector
A sourced case file for attributed work. It is neither a profile score nor a verdict about this researcher.
Attributed works
A bounded ledger from the Pith paper and imported-work queries. Counts and source confidence stay with each work.
-
2024 Pith paper
EDUE: Expert Disagreement-Guided One-Pass Uncertainty Estimation for Medical Image Segmentation
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Ikboljon Sobirov
- Author position
- 3
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
-
- 1 pith inbound references from cited_work_pith_inbound_counts
-
2024 Pith paper
HuLP: Human-in-the-Loop for Prognosis
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Ikboljon Sobirov
- Author position
- 4
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2024 Pith paper
Advanced Tumor Segmentation in Medical Imaging: An Ensemble Approach for BraTS 2023 Adult Glioma and Pediatric Tumor Tasks
paper citation record paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Ikboljon Sobirov
- Author position
- 5
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
-
- 1 pith inbound references from cited_work_pith_inbound_counts
-
2024 Pith paper
Reinforcement Learning for Solving Stochastic Vehicle Routing Problem with Time Windows
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Ikboljon Sobirov
- Author position
- 2
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2023 Pith paper
Reinforcement Learning for Solving Stochastic Vehicle Routing Problem
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Ikboljon Sobirov
- Author position
- 2
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2023 Pith paper
Structurally Different Neural Network Blocks for the Segmentation of Atrial and Aortic Perivascular Adipose Tissue in Multi-centre CT Angiography Scans
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Ikboljon Sobirov
- Author position
- 1
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2023 Pith paper
Diagnosis and Prognosis of Head and Neck Cancer Patients using Artificial Intelligence
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Ikboljon Sobirov
- Author position
- 1
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2023 Pith paper
MGMT promoter methylation status prediction using MRI scans? An extensive experimental evaluation of deep learning models
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Ikboljon Sobirov
- Author position
- 4
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2022 Pith paper
TMSS: An End-to-End Transformer-based Multimodal Network for Segmentation and Survival Prediction
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Ikboljon Sobirov
- Author position
- 2
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2022 Pith paper
Super Images -- A New 2D Perspective on 3D Medical Imaging Analysis
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Ikboljon Sobirov
- Author position
- 1
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2022 Pith paper
An Ensemble Approach for Patient Prognosis of Head and Neck Tumor Using Multimodal Data
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Ikboljon Sobirov
- Author position
- 3
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2022 Pith paper
Object Detection in Aerial Images: What Improves the Accuracy?
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Ikboljon Sobirov
- Author position
- 2
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
-
2022 Pith paper
Automatic Segmentation of Head and Neck Tumor: How Powerful Transformers Are?
paper paper evidence challenge this paper
Sources and evidence
- Authorship source
- arxiv_oai
- Printed name
- Ikboljon Sobirov
- Author position
- 1
- Identity state
- provisional
- Source confidence
- 0.7
- Review coverage
- Measured: no current Pith review exists.
- Citation counts
- No source count is attached to this work row.
Evidence apparatus
The machinery behind this record. Every lane states whether Pith measured it, did not query it, could not reach it, or withheld it.
| Lane | State | Observed | Boundary and source |
|---|---|---|---|
| identity | Measured | 2 | Canonical identity row plus public typed identifiers. source=authors, author_identifiers |
| papers | Measured | 13 of 13 bounded rows | Rows attributed to this author UUID in the Pith corpus. source=paper_authors |
| works | Measured zero | 0 of 0 bounded rows | Imported works not duplicated by the paper ledger. source=author_works |
| reviews | Measured zero | 0 of 13 bounded rows | Coverage count only. No review outcome is projected onto the person. source=current_verdicts |
| citations | Measured | 2 of 13 bounded rows | Counts remain itemized by work and source. source=cited_works |
| coauthors | Measured | 45 of 13 bounded rows | Shared-work edges from admitted paper rows. source=paper_authors |
| account | Unavailable | No public count of 1 bounded rows | Account metadata is separate from corpus evidence. source=users.author_id |
Public identity sources
-
name variant
Ikboljon Sobirov
Enumerated research scope
- eess.IV9 rows
- cs.AI2 rows
- cs.CV2 rows
- 20225 rows
- 20234 rows
- 20244 rows
Record scope
The work queries are bounded. Missing rows may mean measured zero, an unavailable source, a query that did not run, or private data that Pith withheld. The lane table keeps those cases separate.
Paper findings remain attached to papers. They do not become findings about this researcher.
Self-published account annex
Linked Pith account
Unavailable No public Pith account is linked to this corpus identity.
The account lane is self-published. Linking proves account control only and changes no corpus fact.