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Dongxiang Zhang

Zhejiang University

4 papers hereh-index 395.6k citations141 works total

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

author position
  • middle author3

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

fields
  • cs.CV2
  • cs.CL1
  • physics.ins-det1
affiliations
  • Zhejiang University
same name
  • Dongxiang Zhang — 4 papers
  • Dongxiang Zhang — 2 papers
  • Dongxiang Zhang — 1 paper
  • Dongxiang Zhang — 1 paper
  • Dongxiang Zhang — 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

activity
20172019
most citedHierarchical LSTM with Adjusted Temporal Attention for Video Captioning

36 citations · 36 across the 2 of their papers we have counts for

collaborators

4 papers

cs.CV2019

One Network for Multi-Domains: Domain Adaptive Hashing with Intersectant Generative Adversarial Network

Tao He, Yuan-Fang Li, Lianli Gao +2

With the recent explosive increase of digital data, image recognition and retrieval become a critical practical application. Hashing is an effective solution to this problem, due t…

cs.CL2018

Translating a Math Word Problem to an Expression Tree

Lei Wang, Yan Wang, Deng Cai +2

Sequence-to-sequence (SEQ2SEQ) models have been successfully applied to automatic math word problem solving. Despite its simplicity, a drawback still remains: a math word problem c…

physics.ins-det2018

Beyond the N​ limit of the least squares resolution and the lucky model

Gregorio Landi, Giovanni E. Landi

A very simple Gaussian model is used to illustrate a new fitting result: a linear growth of the resolution with the number N of detecting layers. This rule is well beyond the well-…

cs.CV2017★ 36 cited

Hierarchical LSTM with Adjusted Temporal Attention for Video Captioning

Jingkuan Song, Zhao Guo, Lianli Gao +3

Recent progress has been made in using attention based encoder-decoder framework for video captioning. However, most existing decoders apply the attention mechanism to every genera…

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