Search Results for author:
Found 14 papers, 5 papers with code
Affective Event Classification with Discourse-enhanced Self-training
First, we present a BERT-based model for affective event classification and show that the classifier achieves substantially better performance than a large affective event knowledge base.
Exploiting Unary Relations with Stacked Learning for Relation Extraction
Relation extraction models typically cast the problem of determining whether there is a relation between a pair of entities as a single decision.
Ranked #1 on
Relation Extraction
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Exploring the Intersection of Complex Aesthetics and Generative AI for Promoting Cultural Creativity in Rural China after the Post-Pandemic Era
This paper explores using generative AI and aesthetics to promote cultural creativity in rural China amidst COVID-19's impact.
Geometric Wide-Angle Camera Calibration: A Review and Comparative Study
These tests reveal the strengths and weaknesses of these camera models, as well as the repeatability of these GCC tools.
MDOE: A Spatiotemporal Event Representation Considering the Magnitude and Density of Events
Event-based sensors (e. g., DVS cameras) are capable of higher dynamic range, higher temporal resolution, lower time latency, and better power efficiency compared to conventional devices (e. g., RGB cameras).
PLAtE: A Large-scale Dataset for List Page Web Extraction
Recently, neural models have been leveraged to significantly improve the performance of information extraction from semi-structured websites.
Continuous-Time Spatiotemporal Calibration of a Rolling Shutter Camera---IMU System
To this end, we develop a calibration method for a RS-camera-IMU system with continuous-time B-splines by using a calibration target.
Combining Graph Neural Networks with Expert Knowledge for Smart Contract Vulnerability Detection
Then, we propose a novel temporal message propagation network to extract the graph feature from the normalized graph, and combine the graph feature with designed expert patterns to yield a final detection system.
Signal Acquisition of Luojia-1A Low Earth Orbit Navigation Augmentation System with Software Defined Receiver
The performance of those integration algorithms on expanding the successful acquisition time range is verified by the real data collected from the Luojia-1A satellite.
Evolutionary Architecture Search for Graph Neural Networks
In particular, Neural Architecture Search (NAS) has seen significant attention throughout the AutoML research community, and has pushed forward the state-of-the-art in a number of neural models to address grid-like data such as texts and images.
Inertial Sensing Meets Artificial Intelligence: Opportunity or Challenge?
Recently, the emergence of chip-level inertial sensors has expanded the relevant applications from positioning, navigation, and mobile mapping to location-based services, unmanned systems, and transportation big data.
Exploring the Role of Context to Distinguish Rhetorical and Information-Seeking Questions
Social media posts often contain questions, but many of the questions are rhetorical and do not seek information.
Deep Reinforcement Learning (DRL): Another Perspective for Unsupervised Wireless Localization
However, it is challenging to use low-cost IoT devices for robust unsupervised localization (i. e., localization without training data that have known location labels).
Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation
Compared to the related surveys, this paper has a more comprehensive and state-of-the-art review on IoT localization methods, an original review on IoT localization error sources and mitigation, an original review on IoT localization performance evaluation, and a more comprehensive review of IoT localization applications, opportunities, and challenges.
Networking and Internet Architecture Signal Processing
