Search Results for author:
Found 14 papers, 1 papers with code
Data Distribution Dynamics in Real-World WiFi-Based Patient Activity Monitoring for Home Healthcare
This paper examines the application of WiFi signals for real-world monitoring of daily activities in home healthcare scenarios.
Review of the Learning-based Camera and Lidar Simulation Methods for Autonomous Driving Systems
This paper reviews the current state-of-the-art in learning-based sensor simulation methods and validation approaches, focusing on two main types of perception sensors: cameras and Lidars.
A performance characteristic curve for model evaluation: the application in information diffusion prediction
We propose a metric based on information entropy to quantify the randomness in diffusion data, then identify a scaling pattern between the randomness and the prediction accuracy of the model.
A 137.5 TOPS/W SRAM Compute-in-Memory Macro with 9-b Memory Cell-Embedded ADCs and Signal Margin Enhancement Techniques for AI Edge Applications
In this paper, we propose a high-precision SRAM-based CIM macro that can perform 4x4-bit MAC operations and yield 9-bit signed output.
An Interpretable Loan Credit Evaluation Method Based on Rule Representation Learner
More importantly, our model is used to test the correctness of the explanations generated by the post-hoc method, the results show that the post-hoc method is not always reliable.
Author Name Disambiguation via Heterogeneous Network Embedding from Structural and Semantic Perspectives
Our proposal performs better in terms of name disambiguation accuracy compared with baselines and the ablation experiments demonstrate the improvement by feature selection and the meta-path level attention in our method.
MSCET: A Multi-Scenario Offloading Schedule for Biomedical Data Processing and Analysis in Cloud-Edge-Terminal Collaborative Vehicular Networks
The vehicles can offload the computation intensive tasks to the cloud to save the resource of edge.
CCasGNN: Collaborative Cascade Prediction Based on Graph Neural Networks
Cascade prediction aims at modeling information diffusion in the network.
Independent Asymmetric Embedding for Information Diffusion Prediction on Social Networks
The prediction for information diffusion on social networks has great practical significance in marketing and public opinion control.
The evolution of network controllability in growing networks
The study of network structural controllability focuses on the minimum number of driver nodes needed to control a whole network.
Physics and Society
From syntactic structure to semantic relationship: hypernym extraction from definitions by recurrent neural networks using the part of speech information
The hyponym-hypernym relation is an essential element in the semantic network.
Measuring similarity in co-occurrence data using ego-networks
Measuring similarity of entities is one of the important tasks, which can usually be achieved using a network-based approach.
TRIC-track: Tracking by Regression With Incrementally Learned Cascades
This paper proposes a novel approach to part-based tracking by replacing local matching of an appearance model by direct prediction of the displacement between local image patches and part locations.
Dictionary learning based image enhancement for rarity detection
Image enhancement is an important image processing technique that processes images suitably for a specific application e. g. image editing.
