Confidence-Aware Spatial-Temporal Attention Graph Convolutional Network for Skeleton-Based Expert-Novice Level Classification-Reference-Cited by-同舟云学术

Confidence-Aware Spatial-Temporal Attention Graph Convolutional Network for Skeleton-Based Expert-Novice Level Classification

Published:2024-04-14 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Seino Tatsuki¹,Saito Naoki¹,Ogawa Takahiro¹,Asamizu Satoshi²,Haseyama Miki¹

Affiliation:

1. Hokkaido University,Japan

2. Kushiro College,National Institute of Technology,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10445798/10445803/10445994.pdf?arnumber=10445994

Reference24 articles.

1. Novice to Expert: An Exploration of How Professionals Learn

2. Differentiating Surgeons’ Expertise solely by Eye Movement Features

Novice and Expert Anesthesiologists’ Eye-Tracking Metrics During Simulated Epidural Block: A Preliminary, Brief Observational Report

4. Prediction of Second Language Proficiency Based on Electroencephalographic Signals Measured While Listening to Natural Speech

5. Deffrences between expert and novice gymnasts performance of a counter movement forward in flight on uneven bars;Huchez;Science of Gymnastics Journal,2016

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