25 citations · 65 across the 9 of their papers we have counts for
8 papers
Tree-VQ: Progressive Image Compression from Pretrained Vector Quantizers
Xinkun Wang, Tianyi Xu, Qingyu Luo +4
Progressive image compression requires a single embedded representation whose received prefixes can be decoded without re-encoding the source. Modern vector-quantized (VQ) image mo…
Complex Scene Classification of PolSAR Imagery based on a Self-paced Learning Approach
Wenshuai Chen, Shuiping Gou, Xinlin Wang +3
Existing polarimetric synthetic aperture radar (PolSAR) image classification methods cannot achieve satisfactory performance on complex scenes characterized by several types of lan…
Multiple Instance Hybrid Estimator for Hyperspectral Target Characterization and Sub-pixel Target Detection
Changzhe Jiao, Chao Chen, Ronald G. McGarvey +3
The Multiple Instance Hybrid Estimator for discriminative target characterization from imprecisely labeled hyperspectral data is presented. In many hyperspectral target detection p…
Multiple Instance Dictionary Learning for Beat-to-Beat Heart Rate Monitoring from Ballistocardiograms
Changzhe Jiao, Bo-Yu Su, Princess Lyons +3
A multiple instance dictionary learning approach, Dictionary Learning using Functions of Multiple Instances (DL-FUMI), is used to perform beat-to-beat heart rate estimation and to…
Multiple Instance Hybrid Estimator for Learning Target Signatures
Changzhe Jiao, Alina Zare
Signature-based detectors for hyperspectral target detection rely on knowing the specific target signature in advance. However, target signature are often difficult or impossible t…
Multiple Instance Hyperspectral Target Characterization
Alina Zare, Changzhe Jiao, Taylor Glenn
In this paper, two methods for multiple instance target characterization, MI-SMF and MI-ACE, are presented. MI-SMF and MI-ACE estimate a discriminative target signature from imprec…
Heart Beat Characterization from Ballistocardiogram Signals using Extended Functions of Multiple Instances
Changzhe Jiao, Princess Lyons, Alina Zare +2
A multiple instance learning (MIL) method, extended Function of Multiple Instances (FUMI), is applied to ballistocardiogram (BCG) signals produced by a hydraulic bed sensor. The…
Multiple Instance Dictionary Learning using Functions of Multiple Instances
Changzhe Jiao, Alina Zare
A multiple instance dictionary learning method using functions of multiple instances (DL-FUMI) is proposed to address target detection and two-class classification problems with in…