Scene graph generation aims to detect visual relationship triplets, (sub...
Fueled by deep learning, computer-aided diagnosis achieves huge advances...
Relation extraction (RE) aims to extract relations from sentences and
do...
Distantly supervised named entity recognition (DS-NER) has been proposed...
Existing adherent raindrop removal methods focus on the detection of the...
The DocRED dataset is one of the most popular and widely used benchmarks...
Carotid arteries vulnerable plaques are a crucial factor in the screenin...
Document-level Relation Extraction (DRE) aims to recognize the relations...
Aspect-based sentiment analysis (ABSA) is an emerging fine-grained senti...
Aspect Sentiment Triplet Extraction (ASTE) is the most recent subtask of...
Ultrasound scanning is essential in several medical diagnostic and
thera...
Low-dose CT has been a key diagnostic imaging modality to reduce the
pot...
It has been shown that named entity recognition (NER) could benefit from...
Deep neural networks have been widely used in image denoising during the...
Volatility asymmetry is a hot topic in high-frequency financial market. ...
Loss function is crucial for model training and feature representation
l...
Aspect based sentiment analysis, predicting sentiment polarity of given
...
Aspect Sentiment Triplet Extraction (ASTE) is the task of extracting the...
Pragmatics studies how context can contribute to language meanings [1]. ...
In recent years, artificial intelligence (AI) has aroused much attention...
Target-based sentiment analysis or aspect-based sentiment analysis (ABSA...
In recent years, voice knowledge sharing and question answering (Q&A)
pl...
Feature extraction plays a significant part in computer vision tasks. In...
Patient-specific cranial implants are important and necessary in the sur...
In the orthognathic surgery, dental splints are important and necessary ...
This paper presents a generalized integrated framework of semi-automatic...