activity
20142023
most citedAn Attentive-based Generative Model for Medical Image Synthesis

21 citations · 23 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV202321 cited

An Attentive-based Generative Model for Medical Image Synthesis

Jiayuan Wang, Q. M. Jonathan Wu, Farhad Pourpanah

Magnetic resonance (MR) and computer tomography (CT) imaging are valuable tools for diagnosing diseases and planning treatment. However, limitations such as radiation exposure and…

cs.CV2021

Projected Sliced Wasserstein Autoencoder-based Hyperspectral Images Anomaly Detection

Yurong Chen, Hui Zhang, Yaonan Wang +2

Anomaly detection (AD) has been an active research area in various domains. Yet, the increasing data scale, complexity, and dimension turn the traditional methods into challenging.…

cs.CV2014

High Frequency Content based Stimulus for Perceptual Sharpness Assessment in Natural Images

Ashirbani Saha, Q. M. Jonathan Wu

A blind approach to evaluate the perceptual sharpness present in a natural image is proposed. Though the literature demonstrates a set of variegated visual cues to detect or evalua…

cs.CV20142 cited

Full-reference image quality assessment by combining global and local distortion measures

Ashirbani Saha, Q. M. Jonathan Wu

Full-reference image quality assessment (FR-IQA) techniques compare a reference and a distorted/test image and predict the perceptual quality of the test image in terms of a scalar…

cs.NE2014

Pulling back error to the hidden-node parameter technology: Single-hidden-layer feedforward network without output weight

Yimin Yang, Q. M. Jonathan Wu, Guangbin Huang +1

According to conventional neural network theories, the feature of single-hidden-layer feedforward neural networks(SLFNs) resorts to parameters of the weighted connections and hidde…