Výsledky vyhledávání - "Duan, Chaojing"

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Interpretation of Intracardiac Electrograms Through Textual Representations

Autor: Han, William Jongwon, Gomez, Diana, Alok, Avi, Duan, Chaojing, Rosenberg, Michael A., Weber, Douglas, Liu, Emerson, Zhao, Ding

Understanding the irregular electrical activity of atrial fibrillation (AFib) has been a key challenge in electrocardiography. For serious cases of AFib, catheter ablations are performed to collect intracardiac electrograms (EGMs). EGMs offer intrica

Externí odkaz: http://arxiv.org/abs/2402.01115

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Automated Cardiovascular Record Retrieval by Multimodal Learning between Electrocardiogram and Clinical Report

Autor: Qiu, Jielin, Zhu, Jiacheng, Liu, Shiqi, Han, William, Zhang, Jingqi, Duan, Chaojing, Rosenberg, Michael, Liu, Emerson, Weber, Douglas, Zhao, Ding

Automated interpretation of electrocardiograms (ECG) has garnered significant attention with the advancements in machine learning methodologies. Despite the growing interest, most current studies focus solely on classification or regression tasks, wh

Externí odkaz: http://arxiv.org/abs/2304.06286

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Deep Unsupervised Learning of 3D Point Clouds via Graph Topology Inference and Filtering

Autor: Chen, Siheng, Duan, Chaojing, Yang, Yaoqing, Li, Duanshun, Feng, Chen, Tian, Dong

We propose a deep autoencoder with graph topology inference and filtering to achieve compact representations of unorganized 3D point clouds in an unsupervised manner. Many previous works discretize 3D points to voxels and then use lattice-based metho

Externí odkaz: http://arxiv.org/abs/1905.04571

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3D Point Cloud Denoising via Deep Neural Network based Local Surface Estimation

Autor: Duan, Chaojing, Chen, Siheng, Kovacevic, Jelena

We present a neural-network-based architecture for 3D point cloud denoising called neural projection denoising (NPD). In our previous work, we proposed a two-stage denoising algorithm, which first estimates reference planes and follows by projecting

Externí odkaz: http://arxiv.org/abs/1904.04427

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Weighted Multi-projection: 3D Point Cloud Denoising with Estimated Tangent Planes

Autor: Duan, Chaojing, Chen, Siheng, Kovačević, Jelena

As a collection of 3D points sampled from surfaces of objects, a 3D point cloud is widely used in robotics, autonomous driving and augmented reality. Due to the physical limitations of 3D sensing devices, 3D point clouds are usually noisy, which infl

Externí odkaz: http://arxiv.org/abs/1807.00253

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