7,744 Result(s)
within
Chapter
Conference Paper
Lu**g Chen
English
Information Systems Applications (incl. Internet)
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Chapter and Conference Paper
Learning 3D Semantics From Pose-Noisy 2D Images with Hierarchical Full Attention Network
We propose a novel framework to learn 3D point cloud semantics from 2D multi-view image observations containing pose errors. Normally, LiDAR point cloud and RGB images are captured in standard automated-drivin...
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Chapter and Conference Paper
Crowd Intelligence Driven Design Framework Based on Perception-Retrieval Cognitive Mechanism
Currently, the use of crowd intelligence in which the knowledge from different disciplines is integrated for complex product design has attracted increasing attention from both academia and industry. However, ...
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Chapter and Conference Paper
Syntax-Aware Transformer for Sentence Classification
Sentence classification is a significant task in natural language processing (NLP) and is applied in many fields. The syntactic and semantic properties of words and phrases often determine the success of sente...
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Chapter and Conference Paper
InDNI: An Infection Time Independent Method for Diffusion Network Inference
Diffusion network inference aims to reveal the message propagation process among users and has attracted many research interests due to the fundamental role it plays in some real applications, such as rumor-sp...
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Chapter and Conference Paper
Towards a Requirements Co-engineering Improvement Framework: Supporting Digital Delivery Methods in Complex Infrastructure Projects
To support the delivery of cyber-physical systems of complex infrastructure assets, different requirements (e.g., physical system requirements, asset information requirements) must be developed and managed pro...
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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...
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Chapter and Conference Paper
Strong Gravitational Lensing Parameter Estimation with Vision Transformer
Quantifying the parameters and corresponding uncertainties of hundreds of strongly lensed quasar systems holds the key to resolving one of the most important scientific questions: the Hubble constant ( ...
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Chapter and Conference Paper
Chameleon DNN Watermarking: Dynamically Public Model Ownership Verification
Deep neural network (DNN) has made unprecedented leaps in functionality and usefulness in the past few years, revolutionizing various promising fields such as image recognition and machine translation. The tra...
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Chapter and Conference Paper
Mixed-Domain Training Improves Multi-mission Terrain Segmentation
Planetary rover missions must utilize machine learning-based perception to continue extra-terrestrial exploration with little to no human presence. Martian terrain segmentation has been critical for rover navi...
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Chapter and Conference Paper
Image Illumination Enhancement for Construction Worker Pose Estimation in Low-light Conditions
Many construction scenes feature low-light work, such as nighttime construction and tunnel construction. Poor lighting and low visibility will increase the risk of site accidents. One of the leading causes of ...
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Chapter and Conference Paper
Human-Vehicle Cooperative Visual Perception for Autonomous Driving Under Complex Traffic Environments
Human-vehicle cooperative driving has become one of the critical stages to achieve a higher level of driving automation. For an autonomous driving system, the complex traffic environments bring great challenge...
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Chapter and Conference Paper
Improving Contrastive Learning on Visually Homogeneous Mars Rover Images
Contrastive learning has recently demonstrated superior performance to supervised learning, despite requiring no training labels. We explore how contrastive learning can be applied to hundreds of thousands of ...
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Chapter and Conference Paper
SIM2E: Benchmarking the Group Equivariant Capability of Correspondence Matching Algorithms
Correspondence matching is a fundamental problem in computer vision and robotics applications. Solving correspondence matching problems using neural networks has been on the rise recently. Rotation-equivarianc...
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Chapter and Conference Paper
Spatial-Slice Feature Learning Using Visual Transformer and Essential Slices Selection Module for COVID-19 Detection of CT Scans in the Wild
Computed tomography (CT) imaging could be convenient for diagnosing various diseases. However, the CT images could be diverse since their resolution and number of slices are determined by the machine and its s...
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Chapter and Conference Paper
A Deep Wavelet Network for High-Resolution Microscopy Hyperspectral Image Reconstruction
Microscopy hyperspectral imaging (MHSI) integrates conventional imaging with spectroscopy to capture images through numbers of narrow spectral bands, and has attracted much attention in histopathology image an...
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Chapter and Conference Paper
On Mitigating Hard Clusters for Face Clustering
Face clustering is a promising way to scale up face recognition systems using large-scale unlabeled face images. It remains challenging to identify small or sparse face image clusters that we call hard cluster...
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Chapter and Conference Paper
DnA: Improving Few-Shot Transfer Learning with Low-Rank Decomposition and Alignment
Self-supervised (SS) learning has achieved remarkable success in learning strong representation for in-domain few-shot and semi-supervised tasks. However, when transferring such representations to downstream t...
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Chapter and Conference Paper
Evaluation of the Effect of Voice Technology in a Game Teaching E-Book on English Learning
The progress of modern technology has led to diversified teaching methods. Currently, many teaching tools are gradually being combined with technology to create interactive experiences that differ from those o...
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Chapter and Conference Paper
Definition-Augmented Jointly Training Framework for Intention Phrase Mining
We propose to mine intention phrases from large numbers of queries, for enabling rich query interpretation that identifies both query intentions and associated intention types. We formalize the notion of inten...
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Chapter and Conference Paper
An Optimization Algorithm for Extractive Multi-document Summarization Based on Association of Sentences
Designing of automatic summary extraction technology becomes more and more important as the number of documents increasing rapidly. At present, the indicators that are often used for summary evaluation includi...
