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Xiaozhou Ye

4 papers here

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

author position
  • first author2
  • middle author2

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

fields
  • cs.CV1
  • cs.LG1
  • cs.NI1
  • eess.SP1
ORCID 0000-0001-5668-9941
same name
  • Xiaozhou Ye — 2 papers
  • Xiaozhou Ye — 1 paper, h 2
  • Xiaozhou Ye — 1 paper

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 citedAdaptiveNet: Post-deployment Neural Architecture Adaptation for Diverse Edge Environments

2 citations · 5 across the 4 of their papers we have counts for

collaborators

4 papers

eess.SP2024★ 2 cited

Cross-user activity recognition using deep domain adaptation with temporal relation information

Xiaozhou Ye, Waleed H. Abdulla, Nirmal Nair +1

Human Activity Recognition (HAR) is a cornerstone of ubiquitous computing, with promising applications in diverse fields such as health monitoring and ambient assisted living. Desp…

cs.CV2024

Deep Generative Domain Adaptation with Temporal Relation Knowledge for Cross-User Activity Recognition

Xiaozhou Ye, Kevin I-Kai Wang

In human activity recognition (HAR), the assumption that training and testing data are independent and identically distributed (i.i.d.) often fails, particularly in cross-user scen…

cs.NI2023★ 1 cited

6G Network Operation Support System

Ye Ouyang, Yaqin Zhang, Xiaozhou Ye +7

6G is the next-generation intelligent and integrated digital information infrastructure, characterized by ubiquitous interconnection, native intelligence, multi-dimensional percept…

cs.LG2023★ 2 cited

AdaptiveNet: Post-deployment Neural Architecture Adaptation for Diverse Edge Environments

Hao Wen, Yuanchun Li, Zunshuai Zhang +5

Deep learning models are increasingly deployed to edge devices for real-time applications. To ensure stable service quality across diverse edge environments, it is highly desirable…

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