64 citations · 232 across the 12 of their papers we have counts for
12 papers
RSPrompter: Learning to Prompt for Remote Sensing Instance Segmentation based on Visual Foundation Model
Keyan Chen, Chenyang Liu, Hao Chen +4
Leveraging the extensive training data from SA-1B, the Segment Anything Model (SAM) demonstrates remarkable generalization and zero-shot capabilities. However, as a category-agnost…
Continuous Remote Sensing Image Super-Resolution based on Context Interaction in Implicit Function Space
Keyan Chen, Wenyuan Li, Sen Lei +4
Despite its fruitful applications in remote sensing, image super-resolution is troublesome to train and deploy as it handles different resolution magnifications with separate model…
Semantic-aware Dense Representation Learning for Remote Sensing Image Change Detection
Hao Chen, Wenyuan Li, Song Chen +1
Supervised deep learning models depend on massive labeled data. Unfortunately, it is time-consuming and labor-intensive to collect and annotate bitemporal samples containing desire…
Partially Explicit Time Discretization for Nonlinear Time Fractional Diffusion Equations
Wenyuan Li, Anatoly Alikhanov, Yalchin Efendiev +1
Nonlinear time fractional partial differential equations are widely used in modeling and simulations. In many applications, there are high contrast changes in media properties. For…
Contrast-independent partially explicit time discretizations for nonlinear multiscale problems
Eric T. Chung, Yalchin Efendiev, Wing Tat Leung +1
This work continues a line of works on developing partially explicit methods for multiscale problems. In our previous works, we have considered linear multiscale problems, where th…
Geographical Knowledge-driven Representation Learning for Remote Sensing Images
Wenyuan Li, Keyan Chen, Hao Chen +1
The proliferation of remote sensing satellites has resulted in a massive amount of remote sensing images. However, due to human and material resource constraints, the vast majority…
A Multi-resolution Model for Histopathology Image Classification and Localization with Multiple Instance Learning
Jiayun Li, Wenyuan Li, Anthony Sisk +4
Histopathological images provide rich information for disease diagnosis. Large numbers of histopathological images have been digitized into high resolution whole slide images, open…
A Social Search Model for Large Scale Social Networks
Yunzhong He, Wenyuan Li, Liang-Wei Chen +4
With the rise of social networks, information on the internet is no longer solely organized by web pages. Rather, content is generated and shared among users and organized around t…
Semi-supervised Learning using Adversarial Training with Good and Bad Samples
Wenyuan Li, Zichen Wang, Yuguang Yue +4
In this work, we investigate semi-supervised learning (SSL) for image classification using adversarial training. Previous results have illustrated that generative adversarial netwo…
An attention-based multi-resolution model for prostate whole slide imageclassification and localization
Jiayun Li, Wenyuan Li, Arkadiusz Gertych +3
Histology review is often used as the `gold standard' for disease diagnosis. Computer aided diagnosis tools can potentially help improve current pathology workflows by reducing exa…
Semi-supervised learning based on generative adversarial network: a comparison between good GAN and bad GAN approach
Wenyuan Li, Zichen Wang, Jiayun Li +3
Recently, semi-supervised learning methods based on generative adversarial networks (GANs) have received much attention. Among them, two distinct approaches have achieved competiti…
Semi-supervised Rare Disease Detection Using Generative Adversarial Network
Wenyuan Li, Yunlong Wang, Yong Cai +3
Rare diseases affect a relatively small number of people, which limits investment in research for treatments and cures. Developing an efficient method for rare disease detection is…