74 Result(s)
within
**jia Wu
Artificial Intelligence
-
Article
Survey and open problems in privacy-preserving knowledge graph: merging, query, representation, completion, and applications
Knowledge Graph (KG) has attracted more and more companies’ attention for its ability to connect different types of data in meaningful ways and support rich data services. However, due to privacy concerns, dif...
-
Article
Open AccessSimultaneous instance pooling and bag representation selection approach for multiple-instance learning (MIL) using vision transformer
In multiple-instance learning (MIL), the existing bag encoding and attention-based pooling approaches assume that the instances in the bag have no relationship among them. This assumption is unsuited, as the i...
-
Article
A novel lightweight multi-dimension feature fusion network for single-image super-resolution reconstruction
In recent years, due to the powerful feature extraction capabilities of convolutional neural networks (CNNs), many single-image super-resolution (SISR) methods based on CNN have achieved remarkable results. Ho...
-
Article
Introduction to the special issue on recent advances in graph learning: theory, algorithms, applications, and systems
-
Article
Data-Free Quantization with Accurate Activation Clip** and Adaptive Batch Normalization
Data-free quantization compresses the neural network to low bit-width without access to original training data. Most existing data-free quantization methods cause severe performance degradation due to inaccura...
-
Article
Rethinking the Value of Local Feature Fusion in Convolutional Neural Networks
Traditional CNN head for classification tasks typically consists of a global average pooling layer before the last fully-connected classifier. However, such a simple and light-weighted head lacks the ability o...
-
Article
Numerical solution of ruin probability of continuous time model based on optimal adaptive particle swarm optimization-triangular neural network algorithm
In this paper, we study numerical solution of ruin probability of continuous time model. We develop an effective optimal adaptive particle swarm optimization-triangular neural network (PSO-TNN), which consists...
-
Article
Efficient hyperparameters optimization through model-based reinforcement learning with experience exploiting and meta-learning
Hyperparameter optimization plays a significant role in the overall performance of machine learning algorithms. However, the computational cost of algorithm evaluation can be extremely high for complex algorit...
-
Article
Deep spatial–temporal structure learning for rumor detection on Twitter
The widespread of rumors on social media, carrying unreal or even malicious information, brings negative effects on society and individuals, which makes the automatic detection of rumors become particularly im...
-
Chapter and Conference Paper
A Multimodal Text Block Segmentation Framework for Photo Translation
Nowadays, with the vigorous development of OCR (Optical Character Recognition) and machine translation, photo translation technology brings great convenience to people’s life and study. However, when translati...
-
Chapter and Conference Paper
BiblioEngine: An AI-Empowered Platform for Disease Genetic Knowledge Mining
Recent decades have seen significant advancements in contemporary genetic research with the aid of artificial intelligence (AI) techniques. However, researchers lack a comprehensive platform for fully exploiti...
-
Chapter and Conference Paper
Brain Tumor Synthetic Data Generation with Adaptive StyleGANs
Generative models have been very successful over the years and have received significant attention for synthetic data generation. As deep learning models are getting more and more complex, they require large a...
-
Chapter and Conference Paper
End-to-End Multilingual Text Recognition Based on Byte Modeling
Nowadays, multilingual text recognition is more and more widely used in computer vision. However, in practical applications, the independent modeling of each language cannot make full use of the information be...
-
Chapter and Conference Paper
Vision-Language Adaptive Mutual Decoder for OOV-STR
Recent works have shown huge success of deep learning models for common in vocabulary (IV) scene text recognition. However, in real-world scenarios, out-of-vocabulary (OOV) words are of great importance and SO...
-
Chapter and Conference Paper
EmoKnow: Emotion- and Knowledge-Oriented Model for COVID-19 Fake News Detection
Content-based methods are inadequate for detecting fake news related to COVID-19 due to the complexity of this domain. Some studies integrate the social context information of the news to improve performance. ...
-
Chapter and Conference Paper
ParaNet:Parallel Networks with Pre-trained Models for Text Classification
The application of linguistic knowledge derived from pre-trained language models has demonstrated considerable potential in text classification tasks. Despite this, effectively learning the distance between sa...
-
Chapter and Conference Paper
A Contextual Information-Augmented Probabilistic Case-Based Reasoning Model for Knowledge Graph Reasoning
Knowledge Graph Reasoning (KGR) is one effective method to improve incompleteness and sparsity problems, which infers new knowledge based on existing knowledge. Although the probabilistic case-based reasoning ...
-
Chapter and Conference Paper
Discriminative Graph-Level Anomaly Detection via Dual-Students-Teacher Model
Different from the current node-level anomaly detection task, the goal of graph-level anomaly detection is to find abnormal graphs that significantly differ from others in a graph set. Due to the scarcity of r...
-
Article
A novel feature-based model for zero-shot object detection with simulated attributes
Zero-shot object detection (ZSD) has recently been proposed for detecting objects whose categories have never been seen during training. Existing ZSD works have some drawbacks: (a) the end-to-end methods sacri...
-
Article
Efficacy prediction based on attribute and multi-source data collaborative for auxiliary medical system in develo** countries
Non-small cell lung cancer is one of the acute diseases threatening human life. In many develo** countries, there are medical problems such as large populations, underdeveloped technologies, and lack of reso...
