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Yuanjie Yu

dblp:230/4262 · DBLP profile ↗
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3ranked-venue papers
0as first author
3since 2021 · last 2025
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 3 since 2021Systems, architecture and hardware · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Segmentation and scene understanding · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › Segmentation and scene understanding › image segmentation
efficient segmentation
0.812024
Lite-SAM Is Actually What You Need for Segment Everything · ECCV (34) 2024
Computer vision › Segmentation and scene understanding › prompt-based segmentation
segment anything model
0.812024
Lite-SAM Is Actually What You Need for Segment Everything · ECCV (34) 2024

Methods — techniques the papers use, named apart from their topics

knowledge distillation · 0.8
YearPublicationVenuePosition
2025 V-trex: Visual-prompt enhanced detection with attention selection fusion module and random-crop quadruplet loss
Yuanjie Yu, Ningchuan Li, Shengyu Pan, Qun Jin, Jianhai Fu
Knowl. Based Syst.2
2024 Lite-SAM Is Actually What You Need for Segment Everything
Jianhai Fu, Yuanjie Yu, Ningchuan Li, Qichao Chen, Jianping Xiong, Zhiyu Xiang
ECCV (34)2
2022 Data-Driven Kinematic Control Scheme for Cable-Driven Parallel Robots Allowing Collisions
abstract
Cable-Driven Parallel Robots (CDPRs) have been proposed for a variety of applications such as material handling, rehabilitation, and instrumentation. However, the collision-free constraint of CDPRs limits the workspace of CDPRs and the feasible position of anchor points. To address the collision-free constraint of CDPRs, a data-driven kinematic control scheme is developed for CDPRs, enabling a CDPR to control its pose even if suffering collisions between a cable and the base or the end-effector. To deal with the collisions, the data-driven kinematic control scheme utilizes a motion model obtained based on data samples of the motion of the CDPR, rather than the Jacobian matrix of the CDPR, to map a control law in the task space to the time derivative of the length of cables in the joint space. To evaluate the effectiveness of the developed data-driven kinematic control scheme, experiments of controlling a suspended CDPR with two cables allowing collisions are conducted.
Yongwei Zou, Yusheng Hu, Huanhui Cao, Yuchen Xu 0005, Yuanjie Yu, Wenjie Lu 0004, Hao Xiong 0004
IROS5