1 citations · 1 across the 4 of their papers we have counts for
4 papers
Deep Global Clustering for Hyperspectral Image Segmentation: Concepts, Applications, and Open Challenges
Yu-Tang Chang, Pin-Wei Chen, Shih-Fang Chen
Hyperspectral imaging (HSI) analysis faces computational bottlenecks due to massive data volumes that exceed available memory. While foundation models pre-trained on large remote s…
SparseEB-gMCR: A Generative Solver for Extreme Sparse Components with Application to Contamination Removal in GC-MS
Yu-Tang Chang, Shih-Fang Chen
Analytical chemistry instruments provide physically meaningful signals for elucidating analyte composition, and those with high mass or spectral resolution generate signals sparse…
EB-gMCR: Energy-Based Generative Modeling for Signal Unmixing and Multivariate Curve Resolution
Yu-Tang Chang, Shih-Fang Chen
A single measurement of a chemical mixture, a reaction mixture, a natural extract, or a tissue, records the sum of the profiles of the few components it contains, each weighted by…
Design of an basis-projected layer for sparse datasets in deep learning training using gc-ms spectra as a case study
Yu Tang Chang, Shih Fang Chen
Deep learning (DL) models encompass millions or even billions of parameters and learn complex patterns from big data. However, not all data are initially stored in a suitable forma…