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Dequan Wang

University of California, Berkeley

20 papers hereh-index 188.5k citations42 works total

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

author position
  • first author6
  • middle author14

Across the 20 of 20 papers where every author was matched, so the position is known.

fields
  • cs.CV14
  • cs.LG2
  • cs.RO2
  • cs.AI1
  • eess.IV1
affiliations
  • University of California, Berkeley
Homepage
same name
  • Dequan Wang — 7 papers, h 9
  • Dequan Wang — 6 papers, h 3
  • Dequan Wang — 5 papers, h 1
  • Dequan Wang — 5 papers, h 3
  • Dequan Wang — 4 papers, h 2
  • Dequan Wang — 4 papers, h 4

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
20152023
most citedFCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation

692 citations · 1.7k across the 18 of their papers we have counts for

collaborators
Showing 2022Show all

3 papers · 1 filter

cs.RO2022★ 4 cited

MAROAM: Map-based Radar SLAM through Two-step Feature Selection

Dequan Wang, Yifan Duan, Xiaoran Fan +3

In this letter, we propose MAROAM, a millimeter wave radar-based SLAM framework, which employs a two-step feature selection process to build the global consistent map. Specifically…

cs.RO2022★ 3 cited

Decentralized Vehicle Coordination: The Berkeley DeepDrive Drone Dataset and Consensus-Based Models

Fangyu Wu, Dequan Wang, Minjune Hwang +6

A significant portion of roads, particularly in densely populated developing countries, lacks explicitly defined right-of-way rules. These understructured roads pose substantial ch…

cs.LG2022★ 5 cited

GACT: Activation Compressed Training for Generic Network Architectures

Xiaoxuan Liu, Lianmin Zheng, Dequan Wang +9

Training large neural network (NN) models requires extensive memory resources, and Activation Compressed Training (ACT) is a promising approach to reduce training memory footprint.…

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