T
Tzu-Sheng Kuo
Researcher at National Taiwan University
Publications - 7
Citations - 221
Tzu-Sheng Kuo is an academic researcher from National Taiwan University. The author has contributed to research in topics: Haptic technology & Virtual reality. The author has an hindex of 4, co-authored 6 publications receiving 111 citations. Previous affiliations of Tzu-Sheng Kuo include Stanford University.
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Proceedings ArticleDOI
PuPoP: Pop-up Prop on Palm for Virtual Reality
TL;DR: Pop-up Prop on Palm (PuPoP), a light-weight pneumatic shape-proxy interface worn on the palm that pops several airbags up with predefined primitive shapes for grasping that is believed to be a simple yet effective way to convey haptic shapes in VR.
Proceedings ArticleDOI
TilePoP: Tile-type Pop-up Prop for Virtual Reality
Shan-Yuan Teng,Cheng-Lung Lin,Chi-huan Chiang,Tzu-Sheng Kuo,Liwei Chan,Da-Yuan Huang,Bing-Yu Chen +6 more
TL;DR: TilePoP is a new type of pneumatically-actuated interface deployed as floor tiles which dynamically pop up by inflating into large shapes constructing proxy objects for whole-body interactions in Virtual Reality.
Proceedings ArticleDOI
Deep Aggregation Net for Land Cover Classification
TL;DR: A deep aggregation network is proposed for solving land cover classification, which extracts and combines multi-layer features during the segmentation process and introduces soft semantic labels and graph-based fine tuning in this proposed network for improving the segmentations performance.
Proceedings ArticleDOI
AutoFritz: Autocomplete for Prototyping Virtual Breadboard Circuits
Jo-Yu Lo,Da-Yuan Huang,Tzu-Sheng Kuo,Chen-Kuo Sun,Jun Gong,Teddy Seyed,Xing-Dong Yang,Bing-Yu Chen +7 more
TL;DR: This work proposes autocomplete for the design and development of virtual breadboard circuits using software prototyping tools, and implements the system on Fritzing, a popular open source breadboard circuit prototyping software, used by novice makers.
Journal ArticleDOI
DataPerf: Benchmarks for Data-Centric AI Development
Mark Mazumder,Colby R. Banbury,Xiaozhe Yao,Bojan Karlas,W. G. Rojas,Sudnya Diamos,Greg Diamos,Lynn He,Douwe Kiela,David Jurado,David Kanter,Rafael Mosquera,Juan Camilo Galvis Ciro,Lora Aroyo,Bilge Acun,Sabri Eyuboglu,Amirata Ghorbani,Emmett D. Goodman,Tariq Kane,Christine Kirkpatrick,Tzu-Sheng Kuo,Jonas Mueller,Tristan Thrush,Joaquin Vanschoren,Margaret J. Warren,Adina Williams,Serena Yeung,Newsha Ardalani,Praveen Paritosh,Ce Zhang,James Zou,Carole-Jean Wu,Cody Coleman,Andrew Ng,Peter Mattson,Vijay Janapa Reddi +35 more
TL;DR: DataPerf is presented, a benchmark package for evaluating ML datasets and dataset-working algorithms to enable the “data ratchet,” in which training sets will aid in evaluating test sets on the same problems, and vice versa, to generate a virtuous loop that will accelerate development of data-centric AI.