Mingu Kwon

dblp:117/3026 · DBLP profile ↗
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4ranked-venue papers
2as first author
0since 2021 · last 2017
—ORCID · none

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

Artificial intelligence and machine learning · 3 · 1 first-authorSystems, architecture and hardware · 1Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

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
Robot manipulation · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
grasping
0.312017
Grasp quality evaluation and planning for objects with negative curvature · ICRA 2017
Robotics › Robot manipulation › grasping
grasp planning
0.312017
Grasp quality evaluation and planning for objects with negative curvature · ICRA 2017
Robotics › Robot manipulation › grasping
grasp quality evaluation
0.312017
Grasp quality evaluation and planning for objects with negative curvature · ICRA 2017
Robotics › Robot manipulation › grasping
multifingered hand
0.112017
Grasp quality evaluation and planning for objects with negative curvature · ICRA 2017

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

grasp quality metric · 0.3bin picking · 0.3
YearPublicationVenuePosition
2017 Grasp quality evaluation and planning for objects with negative curvature
abstract
We consider the problem of grasping concave objects, i.e., objects whose surface includes regions with negative curvature. When a multifingered hand is used to restrain these objects, these areas can be advantageously used to determine grasps capable of more robustly resisting to external disturbance wrenches. We propose a new grasp quality metric specifically suited for this case, and we use it to inform a grasp planner searching the space of possible grasps. Our findings are validated both in simulation and on a real robot system executing a bin picking task. Experimental validation shows that our method is more effective than those not explicitly considering negative curvature.
Shuo Liu 0006, Mingu Kwon, Zhikang Wang, Stefano Carpin
ICRA4
2014 Emotion recognition based on 3D fuzzy visual and EEG features in movie clips
Giyoung Lee, Mingu Kwon, Swathi Kavuri Sri, Minho Lee 0001
Neurocomputing2
2012 Emotion Understanding in Movie Clips Based on EEG Signal Analysis
Mingu Kwon, Minho Lee 0001
ICONIP (3)1
2012 3D Fuzzy GIST to Analyze Emotional Features in Movies
Mingu Kwon, Minho Lee 0001
IDEAL1