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Yi-Ping Phoebe Chen

Researcher at La Trobe University

Publications -  287
Citations -  5400

Yi-Ping Phoebe Chen is an academic researcher from La Trobe University. The author has contributed to research in topics: Computer science & Feature selection. The author has an hindex of 33, co-authored 268 publications receiving 4206 citations. Previous affiliations of Yi-Ping Phoebe Chen include Fujian Agriculture and Forestry University & Deakin University.

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Book ChapterDOI

A Hybrid Framework Using SOM and Fuzzy Theory for Textual Classification in Data Mining

TL;DR: A hybrid framework combining self-organising map (SOM) and fuzzy theory for textual classification and an amalgamation of SOM and association rule theory is presented, demonstrating the feasibility of applying such processes for data mining and knowledge discovery.
Journal ArticleDOI

GCOTraj: A storage approach for historical trajectory data sets using grid cells ordering

TL;DR: A new indexing and storage approach called GCOTraj is proposed, which partitions a large spatio-temporal data space into multi-dimensional grid cells and orders these grid cells in two different ways, first via traditional space filling curves which are not sensitive to query patterns; and second, via the Graph-Based Ordering approach (GBO) which is a state-of-the-art workload-based ordering technique for multidimensional data.
Proceedings ArticleDOI

TC-GAN: Triangle Cycle-Consistent GANs for Face Frontalization with Facial Features Preserved

TL;DR: The experimental results demonstrate that the proposed novel triangle cycle-consistent generative adversarial networks outperforms the state-of-the-art methods in the preservation of facial identity and expression features during face frontalization.
Journal ArticleDOI

Conformational Features of Topologically Classified RNA Secondary Structures

TL;DR: Results from topological classification suggest that complex pseudoknots are usually some well-known motifs that are themselves complex or the interaction results of some special motifs, even if the required thermodynamic parameters are currently unknown.