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Bin Wang

4 papers hereh-index 8216 citations11 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.CV4
same name
  • Bin Wang — 248 papers, h 54
  • Bin Wang — 35 papers, h 18
  • Bin Wang — 28 papers, h 16
  • Bin Wang — 21 papers, h 6
  • Bin Wang — 17 papers, h 9
  • Bin Wang — 17 papers, h 9

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 citedExploring Multi-Timestep Multi-Stage Diffusion Features for Hyperspectral Image Classification

6 citations · 12 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2023★ 6 cited

Exploring Multi-Timestep Multi-Stage Diffusion Features for Hyperspectral Image Classification

Jingyi Zhou, Jiamu Sheng, Jiayuan Fan +4

The effectiveness of spectral-spatial feature learning is crucial for the hyperspectral image (HSI) classification task. Diffusion models, as a new class of groundbreaking generati…

cs.CV2023★ 2 cited

Performance-aware Approximation of Global Channel Pruning for Multitask CNNs

Hancheng Ye, Bo Zhang, Tao Chen +2

Global channel pruning (GCP) aims to remove a subset of channels (filters) across different layers from a deep model without hurting the performance. Previous works focus on either…

cs.CV2021

Densely Semantic Enhancement for Domain Adaptive Region-free Detectors

Bo Zhang, Tao Chen, Bin Wang +3

Unsupervised domain adaptive object detection aims to adapt a well-trained detector from its original source domain with rich labeled data to a new target domain with unlabeled dat…

cs.CV2021★ 4 cited

Object-aware Long-short-range Spatial Alignment for Few-Shot Fine-Grained Image Classification

Yike Wu, Bo Zhang, Gang Yu +4

The goal of few-shot fine-grained image classification is to recognize rarely seen fine-grained objects in the query set, given only a few samples of this class in the support set.…

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