The photo just want to share
Some individual photos to record life.
Some individual photos to record life.
Exploring the Majestic Landscapes of Banff National Park, Alberta, Canada. This collection captures the untouched beauty of Banff’s rugged mountains and crystal-clear lakes, seen through my lens.
Going out to take photos on a sunny day during my undergraduate studies at the University of Alberta in Edmonton, Canada.
A visual journey through the vibrant and bustling streets of Chongqing, China.
Discover the natural beauty of Elk Island National Park through this photo collection.
A glimpse into the intricate world of miniature sculptures, crafted by the talented artists of the China Academy of Art in Hangzhou, China.
A collection of street photographs taken during my master’s studies in Montreal, Canada, capturing the city’s vibrant urban life.
This set of photos was taken upstairs in my apartment when I was an undergraduate. Taken on the rooftop of Hendrix 31 Apartments, Edmonton, Canada.
Events in Montreal to relive scenes from medieval France. Taken in Montreal, Canada.
The drone aerial photography of a city and countryside, taken in China.
Mountains, woods and animals at different times and locations, but my hometown, taken in Hangzhou, China
Record the moon, sun and sky. Filmed in Canada.
Record the pyramid Biodome in Edmonton, Canada.
Record the zoo in Hangzhou, China.
Commemorating my best friend’s graduation trip in Vancouver, Canada.
Came to Kingston, home to Queen’s University, in Canada.
Published in Smart Multimedia, 2022
This paper introduces SPGNet, a novel deep learning framework for 3D human pose estimation that significantly improves accuracy and efficiency by leveraging spatial projection guidance.
Recommended citation: Wang, Z., Chen, R., Liu, M., Dong, G., & Basu, A. (2022). "SPGNet: Spatial Projection Guided 3D Human Pose Estimation in Low Dimensional Space." Smart Multimedia. [PDF]
Published in NeurIPS 2022 Workshop on Learning from Time Series for Health, 2022
This study utilizes pre-pandemic medical records to enhance the accuracy of ECG-based COVID-19 diagnosis and mortality predictions, offering a novel approach to managing the pandemic.
Recommended citation: Sun, W., Kalmady, S., Sepehrvand, N., Chu, L., Wang, Z., Salimi, A., Hindle, A., Greiner, R., & Kaul, P. (2022). "Improving ECG-based COVID-19 Diagnosis and Mortality Predictions Using Pre-pandemic Medical Records at Population-scale." NeurIPS 2022 Workshop on Learning from Time Series for Health. [PDF]
Published:
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Published:
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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