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researcher

Qiang Li

4 papers here

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

author position
  • middle author1

Across the 1 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV1
  • cs.RO1
  • hep-ph1
  • physics.ins-det1
ORCID 0000-0003-0096-7679
same name
  • Qiang Li — 33 papers, h 41
  • Qiang Li — 32 papers, h 51
  • Qiang Li — 18 papers, h 39
  • Qiang Li — 11 papers
  • Qiang Li — 9 papers
  • Qiang Li — 8 papers

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 citedRobotic Perception with a Large Tactile-Vision-Language Model for Physical Property Inference

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

cs.RO2025★ 1 cited

Robotic Perception with a Large Tactile-Vision-Language Model for Physical Property Inference

Zexiang Guo, Hengxiang Chen, Xinheng Mai +5

Inferring physical properties can significantly enhance robotic manipulation by enabling robots to handle objects safely and efficiently through adaptive grasping strategies. Previ…

physics.ins-det2025

Test of LGAD as Potential Next-Generation μSR Spectrometer Detectors

Yuhang Guo, Qiang Li, Yu Bao +13

Muon Spin Rotation/Relaxation/Resonance (μSR) is a versatile and powerful non-destructive technology for investigating the magnetic properties of materials at the microscopic lev…

hep-ph2025

Novel ∣Vcb​∣ extraction method via boosted bc-tagging with in-situ calibration

Yuzhe Zhao, Congqiao Li, Antonios Agapitos +4

We present a novel method for measuring ∣Vcb​∣ at the LHC using an advanced boosted-jet tagger to identify "bc signatures". By associating boosted W→bc signals…

cs.CV2024

SpirDet: Towards Efficient, Accurate and Lightweight Infrared Small Target Detector

Qianchen Mao, Qiang Li, Bingshu Wang +3

In recent years, the detection of infrared small targets using deep learning methods has garnered substantial attention due to notable advancements. To improve the detection capabi…

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