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Junzhou Huang

4 papers hereh-index 4103 citations8 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CV1
  • q-bio.GN1
same name
  • Junzhou Huang — 10 papers, h 6
  • Junzhou Huang — 3 papers, h 5
  • Junzhou Huang — 2 papers, h 2
  • Junzhou Huang — 1 paper, h 0
  • Junzhou Huang — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators

4 papers

cs.LG2026

Breaking the Correlation Plateau: On the Optimization and Capacity Limits of Attention-Based Regressors

Jingquan Yan, Yuwei Miao, Peiran Yu +1

Attention-based regression models are often trained by jointly optimizing Mean Squared Error (MSE) loss and Pearson correlation coefficient (PCC) loss, emphasizing the magnitude of…

q-bio.GN2026

Histopathology-centered Computational Evolution of Spatial Omics: Integration, Mapping, and Foundation Models

Ninghui Hao, Xinxing Yang, Boshen Yan +7

Spatial omics (SO) technologies enable spatially resolved molecular profiling, while hematoxylin and eosin (H&E) imaging remains the gold standard for morphological assessment in c…

cs.CV2025

AI-Assisted Decision-Making for Clinical Assessment of Auto-Segmented Contour Quality

Biling Wang, Austen Maniscalco, Ti Bai +8

Purpose: This study presents a Deep Learning (DL)-based quality assessment (QA) approach for evaluating auto-generated contours (auto-contours) in radiotherapy, with emphasis on On…

cs.LG2024

CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models

Peng Xia, Ze Chen, Juanxi Tian +21

Artificial intelligence has significantly impacted medical applications, particularly with the advent of Medical Large Vision Language Models (Med-LVLMs), sparking optimism for the…

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