Jinpu's Projects
Applied machine-learning models, including linear regression, random forest regression, convolutional neural networks, and recurrent neural networks to make predictions on cell life.
The project introduced the first system-PigSense to use structural vibration to track animals. The system uses physical knowledge of the structural vibration characteristics caused by pig-activity-induced load changes to recognize different behaviors of the sow and piglets.
Reproduce the results Reproduce the results of 3D semantic instance segmentation with Mask3D
Stanford team and Fortuna team worked together and conducted a formal life cycle assessment of Fortuna coolers.
Config files for my GitHub profile.
A Long-term Probabilistic Forecasting Approach of TBM Operating Parameters based on Deep Learning
A water consumption probability prediction model based on a deep autoregressive model
Classify solid samples according to their diffuse reflectance infrared spectra。
An end-to-end pavement crack detection toolkit is developed based on computer vision
Characterize communities’ air quality and explore the human-induced and environment-induced influence on it
The Sustainable Urban Systems emphasis merges traditional data analytics with complex systems analysis to better inform decisions around the wicked problems of urban development like urban land use, mobility, sustainability and hazard analysis.
An LSTM-based model for TBM performance prediction and the effect of rock mass grade on prediction accuracy
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Django
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Microsoft
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Alibaba
D3
Tencent