Search Results for author:
Found 42 papers, 9 papers with code
OmniColor: A Global Camera Pose Optimization Approach of LiDAR-360Camera Fusion for Colorizing Point Clouds
A Colored point cloud, as a simple and efficient 3D representation, has many advantages in various fields, including robotic navigation and scene reconstruction.
Large Language Model-driven Meta-structure Discovery in Heterogeneous Information Network
We propose a novel REasoning meta-STRUCTure search (ReStruct) framework that integrates LLM reasoning into the evolutionary procedure.
Exploring the Potential of Large Language Models in Artistic Creation: Collaboration and Reflection on Creative Programming
Recently, the potential of large language models (LLMs) has been widely used in assisting programming.
APT-Pipe: A Prompt-Tuning Tool for Social Data Annotation using ChatGPT
To address this, there has been a flurry of research into prompt tuning -- techniques and guidelines that attempt to improve the quality of prompts.
Dream360: Diverse and Immersive Outdoor Virtual Scene Creation via Transformer-Based 360 Image Outpainting
To this end, we propose a transformer-based 360 image outpainting framework called Dream360, which can generate diverse, high-fidelity, and high-resolution panoramas from user-selected viewports, considering the spherical properties of 360 images.
VR PreM+ : An Immersive Pre-learning Branching Visualization System for Museum Tours
We present VR PreM+, an innovative VR system designed to enhance web exploration beyond traditional computer screens.
A Satellite Imagery Dataset for Long-Term Sustainable Development in United States Cities
Especially satellite imagery is a potential data source for studying sustainable urban development.
Efficient Task Offloading Algorithm for Digital Twin in Edge/Cloud Computing Environment
In the era of Internet of Things (IoT), Digital Twin (DT) is envisioned to empower various areas as a bridge between physical objects and the digital world.
Lightweight Modeling of User Context Combining Physical and Virtual Sensor Data
The framework has been used by 3 voluntary users for two weeks, generating a dataset with more than 36K samples and 1331 features.
Attention-based QoE-aware Digital Twin Empowered Edge Computing for Immersive Virtual Reality
In this paper, we tackle this desynchronization using a continual RL framework that facilitates the resource allocation dynamically for MEC-enabled VR content streaming.
Towards AI-Architecture Liberty: A Comprehensive Survey on Designing and Collaborating Virtual Architecture by Deep Learning in the Metaverse
This survey investigates the latest approaches to 3D object generation with deep generative models (DGMs) and summarizes four characteristics of deep-learning generation approaches for virtual architecture.
Can ChatGPT Reproduce Human-Generated Labels? A Study of Social Computing Tasks
We believe this work can open up new lines of analysis and act as a basis for future research into the exploitation of ChatGPT for human annotation tasks.
One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era
Overall, this work is the first to survey ChatGPT with a comprehensive review of its underlying technology, applications, and challenges.
Dataset for predicting cybersickness from a virtual navigation task
This work presents a dataset collected to predict cybersickness in virtual reality environments.
Bi-directional Digital Twin and Edge Computing in the Metaverse
Multi-access edge computing (MEC) provides responsive services to the end users, ensuring an immersive and interactive Metaverse experience.
6G Mobile-Edge Empowered Metaverse: Requirements, Technologies, Challenges and Research Directions
The Metaverse has emerged as the successor of the conventional mobile internet to change people's lifestyles.
Federated Split GANs
Mobile devices and the immense amount and variety of data they generate are key enablers of machine learning (ML)-based applications.
HideNseek: Federated Lottery Ticket via Server-side Pruning and Sign Supermask
Consequently, the training requires high computation cost and a long time to converge while the model performance does not pay off.
Twitter Dataset for 2022 Russo-Ukrainian Crisis
Such information sharing campaigns can range from spreading factual information to propaganda and misinformation.
Towards User-Centered Metrics for Trustworthy AI in Immersive Cyberspace
AI plays a key role in current cyberspace and future immersive ecosystems that pinpoint user experiences.
When Creators Meet the Metaverse: A Survey on Computational Arts
The metaverse, enormous virtual-physical cyberspace, has brought unprecedented opportunities for artists to blend every corner of our physical surroundings with digital creativity.
Exploring System Performance of Continual Learning for Mobile and Embedded Sensing Applications
Our findings suggest that replay with exemplars-based schemes such as iCaRL has the best performance trade-offs, even in complex scenarios, at the expense of some storage space (few MBs) for training examples (1% to 5%).
Mobile Augmented Reality: User Interfaces, Frameworks, and Intelligence
Mobile Augmented Reality (MAR) integrates computer-generated virtual objects with physical environments for mobile devices.
Loss Tolerant Federated Learning
Federated learning has attracted attention in recent years for collaboratively training data on distributed devices with privacy-preservation.
Genetic Meta-Structure Search for Recommendation on Heterogeneous Information Network
To address these challenges, we propose Genetic Meta-Structure Search (GEMS) to automatically optimize meta-structure designs for recommendation on HINs.
Characterizing Student Engagement Moods for Dropout Prediction in Question Pool Websites
Problem-Based Learning (PBL) is a popular approach to instruction that supports students to get hands-on training by solving problems.
Predicting Hyperkalemia in the ICU and Evaluation of Generalizability and Interpretability
While hyperkalemia is often a complication of acute kidney injury (AKI), it also occurs in the absence of AKI.
Automorphic Equivalence-aware Graph Neural Network
Distinguishing the automorphic equivalence of nodes in a graph plays an essential role in many scientific domains, e. g., computational biologist and social network analysis.
DRLE: Decentralized Reinforcement Learning at the Edge for Traffic Light Control in the IoV
To this end, we propose a Decentralized Reinforcement Learning at the Edge for traffic light control in the IoV (DRLE).
Urban Anomaly Analytics: Description, Detection, and Prediction
Urban anomalies may result in loss of life or property if not handled properly.
Edge Intelligence: Architectures, Challenges, and Applications
Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis in locations close to where data is captured based on artificial intelligence.
Marketplace for AI Models
Artificial intelligence shows promise for solving many practical societal problems in areas such as healthcare and transportation.
UrbanRhythm: Revealing Urban Dynamics Hidden in Mobility Data
In this paper, to reveal urban dynamics, we propose a novel system UrbanRhythm to reveal the urban dynamics hidden in human mobility data.
DeepHealth: Review and challenges of artificial intelligence in health informatics
The demand for it in health informatics is also increasing, and we can expect to see the potential benefits of its applications in healthcare.
FaRM: Fair Reward Mechanism for Information Aggregation in Spontaneous Localized Settings (Extended Version)
FaRM uses \textit{(i)} a \emph{report strength score} to remove the risk of random pairing with dishonest reporters, \textit{(ii)} a \emph{consistency score} to measure an agent's history of accurate reports and distinguish valuable reports, \textit{(iii)} a \emph{reliability score} to estimate the probability of an agent to collude with nearby agents and prevents agents from getting swayed, and \textit{(iv)} a \emph{location robustness score} to filter agents who try to participate without being present in the considered setting.
Inflo: News Categorization and Keyphrase Extraction for Implementation in an Aggregation System
The work herein describes a system for automatic news category and keyphrase labeling, presented in the context of our motivation to improve the speed at which a user can find relevant and interesting content within an aggregation platform.
Where's YOUR focus: Personalized Attention
In this work, we present the novel idea of personalized attention prediction and develop Personalized Attention Network (PANet), a convolutional network that predicts saliency in images with personal preference.
Cardea: Context-Aware Visual Privacy Protection from Pervasive Cameras
The growing popularity of mobile and wearable devices with built-in cameras, the bright prospect of camera related applications such as augmented reality and life-logging system, the increased ease of taking and sharing photos, and advances in computer vision techniques have greatly facilitated people's lives in many aspects, but have also inevitably raised people's concerns about visual privacy at the same time.
Semantic homophily in online communication: evidence from Twitter
An important question to researchers and in practice can be tackled, as we present here: understanding the exact mechanisms of interplay between these tendencies and the underlying social network structure.
Motion and audio analysis in mobile devices for remote monitoring of physical activities and user authentication
In this article we propose the use of accelerometer embedded by default in smartphone as a cost-effective, reliable and efficient way to provide remote physical activity monitoring for the elderly and people requiring healthcare service.
A Random Walk Based Model Incorporating Social Information for Recommendations
Collaborative filtering (CF) is one of the most popular approaches to build a recommendation system.
Wisdom of the Crowd: Incorporating Social Influence in Recommendation Models
In this paper, we propose two recommendation models, for individuals and for groups respectively, based on social contagion and social influence network theory.
