Search Results for author:
Found 13 papers, 5 papers with code
Evaluating the Performance of Large Language Models for SDG Mapping (Technical Report)
Given the multi-label nature of the SDG mapping task, we employed metrics such as F1 score, precision, and recall with micro-averaging to evaluate different aspects of the models' performance.
Combining Knowledge Graphs and Large Language Models
The emergence of large language models (LLMs) has greatly improved the performance of these applications, showing astonishing results in language understanding and generation.
Dual Hyperspectral Mamba for Efficient Spectral Compressive Imaging
Experiments verify the benefits of our DHM for HSI reconstruction.
A Rapid Review of Clustering Algorithms
Clustering algorithms aim to organize data into groups or clusters based on the inherent patterns and similarities within the data.
Leveraging Artificial Intelligence Technology for Mapping Research to Sustainable Development Goals: A Case Study
We utilized a similarity measure to map these publications onto Sustainable Development Goals (SDGs).
Style-Guided Shadow Removal
To address this problem, we propose a style-guided shadow removal network (SG-ShadowNet) for better image-style consistency after shadow removal.
Ranked #6 on
Shadow Removal
on ISTD+
CRFormer: A Cross-Region Transformer for Shadow Removal
Aiming to restore the original intensity of shadow regions in an image and make them compatible with the remaining non-shadow regions without a trace, shadow removal is a very challenging problem that benefits many downstream image/video-related tasks.
Sentiment Analysis and Topic Modeling for COVID-19 Vaccine Discussions
The outbreak of the novel Coronavirus Disease 2019 (COVID-19) has lasted for nearly two years and caused unprecedented impacts on people's daily life around the world.
Representation Learning for Short Text Clustering
Effective representation learning is critical for short text clustering due to the sparse, high-dimensional and noise attributes of short text corpus.
From Shadow Generation to Shadow Removal
Shadow removal is a computer-vision task that aims to restore the image content in shadow regions.
Ranked #11 on
Shadow Removal
on ISTD+
Detecting Topic and Sentiment Dynamics Due to COVID-19 Pandemic Using Social Media
The large scale social media posts (e. g., tweets) provide an ideal data source to infer the mental health for people during this pandemic period.
Shadow Removal by a Lightness-Guided Network with Training on Unpaired Data
In this paper, we present a new Lightness-Guided Shadow Removal Network (LG-ShadowNet) for shadow removal by training on unpaired data.
Side Window Filtering
In addition to image filtering, we further show that the SWF principle can be extended to other applications involving the use of a local window.
