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researcher

Dandan Zhu

4 papers hereh-index 12567 citations44 works total

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

author position
  • first author1
  • middle author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • eess.IV1
  • stat.ML1
same name
  • Dandan Zhu — 16 papers, h 7
  • Dandan Zhu — 8 papers, h 3
  • Dandan Zhu — 4 papers, h 2
  • Dandan Zhu — 3 papers, h 3
  • Dandan Zhu — 2 papers, h 2
  • Dandan Zhu — 1 paper, h 1

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

most citedToward Better Understanding of Saliency Prediction in Augmented 360 Degree Videos

3 citations · 4 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2026

FSDC-DETR: A Frequency-Spatial Domain Collaborative DETR for Small Object Detection

Aiwen Liu, Chengguang Zhu, Gang Wang +5

Small object detection (SOD) remains a challenging task in real-world applications. Despite recent advances, existing detectors remain limited by rigid processing that entangle spa…

cs.CV2026

TP-Seg: Task-Prototype Framework for Unified Medical Lesion Segmentation

Jiawei Xu, Qiangqiang Zhou, Dandan Zhu +3

Building a unified model with a single set of parameters to efficiently handle diverse types of medical lesion segmentation has become a crucial objective for AI-assisted diagnosis…

eess.IV2019★ 3 cited

Toward Better Understanding of Saliency Prediction in Augmented 360 Degree Videos

Yucheng Zhu, Xiongkuo Min, DanDan Zhu +5

Augmented reality (AR) overlays digital content onto the reality. In AR system, correct and precise estimations of user's visual fixations and head movements can enhance the qualit…

stat.ML2019★ 1 cited

Deep Unsupervised Clustering with Clustered Generator Model

Dandan Zhu, Tian Han, Linqi Zhou +2

This paper addresses the problem of unsupervised clustering which remains one of the most fundamental challenges in machine learning and artificial intelligence. We propose the clu…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.