Shaohua Wang
Wuhan University
5 Papers
14 Citations
Shaohua Wang is an academic researcher from Wuhan University. The author has contributed to research in topics: Computer science & Mean squared error. The author has an hindex of 2, co-authored 2 publications.
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Papers
Accurate Recognition of Building Rooftops and Assessment of Long-Term Carbon Emission Reduction from Rooftop Solar Photovoltaic Systems Fusing GF-2 and Multi-Source Data
Shaofu Lin,Chang Zhang,Lei Ding,Jing Zhang,Xiang Liu,Guihong Chen,Shaohua Wang,Jinchuan Chai +7 more
TL;DR: Wang et al. as mentioned in this paper proposed a method to assess accurately the potential reduction of long-term carbon emission by installing solar PV on rooftops, which is achieved using the joint action of GF-2 satellite images, Point of Interest (POI) data, and meteorological data.
Human action recognition based on scene semantics
TL;DR: This paper proposed an indoor action recognition method using Kinect based on the semantics of a scene, and a trajectory clustering algorithm for a three-dimensional (3D) scene by combining the different characteristics of people such as the spatial location, movement direction, and speed.
15
Human interaction recognition using spatial-temporal salient feature
TL;DR: A novel method for human interaction recognition based on 3D skeleton data captured by Kinect sensor using hierarchical spatial-temporal saliency-based representation method, which demonstrates that the average recognition accuracy is 90.29%, outperforming methods using other features.
15
A Spatial–Temporal Causal Convolution Network Framework for Accurate and Fine-Grained PM2.5 Concentration Prediction
Shaofu Lin,Junjie Zhao,Jianqiang Li,Xiang Liu,Yumin Zhang,Shaohua Wang,Qiang Mei,Zhuodong Chen,Yuyao Gao +8 more
TL;DR: In this paper , a spatial-temporal causal convolutional network (ST-CCN-PM2.5) was proposed to predict fine-grained PM2-5 concentration in Haikou, China.
Fine-Grained Individual Air Quality Index (IAQI) Prediction Based on Spatial-Temporal Causal Convolution Network: A Case Study of Shanghai
Xiang Liu,Junjie Zhao,Shaofu Lin,Jianqiang Li,Shaohua Wang,Yumin Zhang,Yuyao Gao,Jinchuan Chai +7 more
TL;DR: Wang et al. as mentioned in this paper proposed a spatial-temporal causal convolutional network (ST-CCN-IAQI) model for fine-grained individual air quality index prediction.