113 Result(s)
within
Yongbin **g
Computer Science
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Article
QLDT: adaptive Query Learning for HOI Detection via vision-language knowledge Transfer
Human-object interaction detection can be mainly categorized into two core problems, namely human-object association detection and interaction understanding. Firstly, for association detection, previous method...
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Article
Open AccessIn-depth Correlation Power Analysis Attacks on a Hardware Implementation of CRYSTALS-Dilithium
During the standardisation process of post-quantum cryptography, NIST encourages research on side-channel analysis for candidate schemes. As the recommended lattice signature scheme, CRYSTALS-Dilithium, when i...
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Article
Self-training improves few-shot learning in legal artificial intelligence tasks
As the labeling costs in legal artificial intelligence tasks are expensive. Therefore, it becomes a challenge to utilize low cost to train a robust model. In this paper, we propose a LAIAugment approach, which...
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Article
Open AccessSelf-Enhanced Attention for Image Captioning
Image captioning, which involves automatically generating textual descriptions based on the content of images, has garnered increasing attention from researchers. Recently, Transformers have emerged as the pre...
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Article
Entity alignment based on informative neighbor sampling and multi-embedding graph matching
Entity alignment is an important and necessary step in the process of knowledge fusion, which aims to match entities with the same meaning in different knowledge graphs. In this paper, we propose a novel entit...
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Article
A novel MRC framework for evidence extracts in judgment documents
Evidences are important proofs to support judicial trials. Automatically extracting evidences from judgement documents can be used to assess the trial quality and support “Intelligent Court”. Current evidence ...
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Article
Open AccessAPRE: Annotation-Aware Prompt-Tuning for Relation Extraction
Prompt-tuning has been successfully applied to support classification tasks in natural language processing and has achieved promising performance. The main characteristic of prompt-tuning based classification ...
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Chapter and Conference Paper
Debiasing Medication Recommendation with Counterfactual Analysis
The AI-driven medication recommendation has emerged as a crucial undertaking in the field of healthcare research. Recent literature has focused on leveraging patients’ diagnoses, procedures, and historical vis...
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Chapter and Conference Paper
Optimization of Takagi-Sugeno-Kang Fuzzy Model Based on Differential Evolution with Lévy Flight
In this article, a novel evolutionary algorithm called differential evolution with Lévy flight (DEFL) algorithm was proposed to optimize the Takagi-Sugeno-Kang fuzzy model (TSK fuzzy model) by finding the opti...
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Article
A fine-grained causality extraction model incorporating relative location coding
Popular methods of causality extraction work well for simple and explicit single causal relations, but it remains challenging to extract causal relations from the complex sentences of natural texts due to ambi...
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Article
Online object-level SLAM with dual bundle adjustment
Object-level landmarks enable the SLAM system to construct robust object-keyframe constraints of bundle adjustment and improve the pose estimation performance. In this paper, we present a real-time online obje...
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Article
Open AccessEnhancing non-profiled side-channel attacks by time-frequency analysis
Side-channel analysis (SCA) has become an increasing important method to assess the physical security of cryptographic systems. In the process of SCA, the number of attack data directly determines the performa...
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Article
MACFNet: multi-attention complementary fusion network for image denoising
Recent years, thanks to the prosperous development of deep convolutional neural network, image denoising task has achieved unprecedented achievements. However, previous researches have difficulties in kee** ...
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Article
Feature selection optimized by the artificial immune algorithm based on genome shuffling and conditional lethal mutation
Improving classification performance is an essential goal for various practical applications. Feature selection has become an important data preprocessing step in machine learning systems. However, many effect...
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Article
Deep structural enhanced network for document clustering
Recently, deep document clustering, which employs deep neural networks to learn semantic document representation for clustering purpose, has attracted increasing research interests. Traditional deep document c...
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Article
Transformer networks with adaptive inference for scene graph generation
Understanding a visual scene requires not only identifying single objects in isolation but also inferring the relationships and interactions between object pairs. In this study, we propose a novel scene graph ...
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Article
Open AccessA Boundary Regression Model for Nested Named Entity Recognition
Recognizing named entities (NEs) is commonly treated as a classification problem, and a class tag for a word or an NE candidate in a sentence is predicted. In recent neural network developments, deep structure...
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Chapter and Conference Paper
Improving Learning Outcomes with Pair Teaching StrateFiggy in Higher Education: A Case Study in C Programming Language
Learning outcomes have attracted more and more attention in higher education. Many teaching and learning methods have been invented to improve learning outcomes. Teaching and learning pedagogies will attract i...
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Chapter and Conference Paper
An Experimental Case Study for the Course of ‘Testing Technology and Data Processing’
‘Testing Technology and Data Processing (TTDP)’ is one of the core courses for the undergraduates in mechanical engineering subject. This paper designs an experimental case to improve the students’ abilities i...
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Chapter and Conference Paper
A Learnable Graph Convolutional Neural Network Model for Relation Extraction
Relation extraction is the task of extracting the semantic relationships between two named entities in a sentence. The task relies on semantic dependencies relevant to named entities. Recently, graph convoluti...
