185 Result(s)
within
Hao WU
Computer Science
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Article
Open AccessInfinite families of minimal binary codes via Krawtchouk polynomials
Linear codes play a crucial role in various fields of engineering and mathematics, including data storage, communication, cryptography, and combinatorics. Minimal linear codes, a subset of linear codes, are pa...
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Article
BDNet: a method based on forward and backward convolutional networks for action recognition in videos
Human action recognition analyzes the behavior in a scene according to the spatiotemporal features carried in image sequences. Existing works suffers from ineffective spatial–temporal feature learning. For sho...
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Article
Open AccessDelving into high-quality SVBRDF acquisition: A new setup and method
In this study, we present a new and innovative framework for acquiring high-quality SVBRDF maps. Our approach addresses the limitations of the current methods and proposes a new solution. The core of our metho...
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Article
Natural language processing in educational research: The evolution of research topics
Natural language processing (NLP) has captivated the attention of educational researchers over the past three decades. In this study, a total of 2,480 studies were retrieved through a comprehensive literature ...
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Article
Generative facial prior embedded degradation adaption network for heterogeneous face hallucination
In real-world long-range surveillance systems, thermal face images captured from a distance suffer from low resolution and noise, posing challenges for thermal-to-visible face image translation. Current method...
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Article
Detail-aware image denoising via structure preserved network and residual diffusion model
The rapid development of deep learning has led to significant strides in image denoising research and has achieved advanced denoising performance in terms of distortion metrics. However, most denoising models ...
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Article
TAE: Topic-aware encoder for large-scale multi-label text classification
Convolutional neural networks, recurrent neural networks, and transformers have excelled in representation learning for large-scale multi-label text classification. However, there have been very few works that...
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Article
A decision procedure for string constraints with string/integer conversion and flat regular constraints
String constraint solving is the core of various testing and verification approaches for scripting languages. Among algorithms for solving string constraints, flattening is a well-known approach that is partic...
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Chapter and Conference Paper
A Quantum-Based Attention Mechanism in Scene Text Detection
Attention mechanisms have provided benefits in very many visual tasks, e.g. image classification, object detection, semantic segmentation. However, few attention modules have been proposed specifically for sce...
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Chapter and Conference Paper
TSTD:A Cross-modal Two Stages Network with New Trans-decoder for Point Cloud Semantic Segmentation
In recent years, exploring integrated heterogeneous features architecture has become one of the hot spots in 3D point cloud understanding. However, the efficacy of end-to-end training in enhancing the precisio...
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Chapter and Conference Paper
A General Federated Learning Scheme with Blockchain on Non-IID Data
The security of machine learning has received a lot of attention from the community. Federated learning enables more secure training processes of models in machine learning via local training and parameter int...
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Chapter
Generative Adversarial Network Based Deep Learning Method for Machine Vision Inspection
When deep learning methods are applied to the detection of low contrast LCD surfaces, due to the imbalance between positive and negative samples and the difficulty in detecting micro defects with uneven bright...
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Chapter and Conference Paper
QEA-Net: Quantum-Effects-based Attention Networks
In the past decade, the attention mechanism has played an increasingly important role in computer vision. Such an attention mechanism can be regarded as a dynamic weight adjustment process based on features of...
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Chapter and Conference Paper
Improving Transferability of Adversarial Attacks with Gaussian Gradient Enhance Momentum
Deep neural networks (DNNs) can be susceptible to subtle perturbations that may mislead the model. While adversarial attacks are successful in the white-box setting, they are less effective in the black-box se...
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Chapter and Conference Paper
A Voxel-Based Multiview Point Cloud Refinement Method via Factor Graph Optimization
lidar enables fast reconstruction of the real world using high-precision point cloud maps. It usually requires the pose information (also called trajectory) of point clouds obtained by lidar at different times...
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Chapter and Conference Paper
Applications of Quantum Embedding in Computer Vision
Nowadays, Deep Neural Networks (DNNs) are fundamental to many vision tasks, including large-scale visual recognition. As the primary goal of the DNNs is to characterize complex boundaries of thousands of class...
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Article
Progressive local-to-global vision transformer for occluded face hallucination
Hallucinating a photo-realistic high-resolution (HR) face image from an occluded low-resolution (LR) face image is beneficial for a series of face-related applications. However, previous efforts focused on eit...
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Article
Design of social navigation quality evaluation model based on combined weight
Based on the human–robot interaction behavior of mobile robots in social navigation, this paper proposes a social navigation quality evaluation model based on combined weights for the problems of single indica...
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Article
A discriminative multiple-manifold network for image set classification
Because the distinct advantages of manifold-learning methods for feature extraction, Riemannian manifolds have been used extensively in image recognition tasks in recent years. However, large intra-class varia...
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Article
Dynamic relation learning for link prediction in knowledge hypergraphs
Link prediction for knowledge graphs (KGs), which aims to predict missing facts, has been broadly studied in binary relational KGs. However, real world data contains a large number of high-order interaction pa...
