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Found 8 papers, 3 papers with code
DeconfuseTrack:Dealing with Confusion for Multi-Object Tracking
Moreover, DeconfuseTrack achieves state-of-the-art performance on the MOT17 and MOT20 test sets, significantly outperforms the baseline tracker ByteTrack in metrics such as HOTA, IDF1, AssA.
Location-guided Head Pose Estimation for Fisheye Image
Camera with a fisheye or ultra-wide lens covers a wide field of view that cannot be modeled by the perspective projection.
Code Clone Detection based on Event Embedding and Event Dependency
To address this issue, we propose a code clone detection method based on semantic similarity.
Non-intrusive Balancing Transformation of Highly Stiff Systems with Lightly-damped Impulse Response
Balanced truncation (BT) is a model reduction method that utilizes a coordinate transformation to retain eigen-directions that are highly observable and reachable.
Data-driven reduced-order models via regularized operator inference for a single-injector combustion process
With appropriate regularization and an informed selection of learning variables, the reduced-order models exhibit high accuracy in re-predicting the training regime and acceptable accuracy in predicting future dynamics, while achieving close to a million times speedup in computational cost.
Computational Engineering, Finance, and Science J.2
Learning physics-based reduced-order models for a single-injector combustion process
The machine learning perspective brings the flexibility to use transformed physical variables to define the POD basis.
LoadCNN: A Low Training Cost Deep Learning Model for Day-Ahead Individual Residential Load Forecasting
As a consequence, the deep learning methods are difficult to be popularized and applied in the real smart grid environment.
A Distributed One-Step Estimator
A potential application of the one-step approach is that one can use multiple machines to speed up large scale statistical inference with little compromise in the quality of estimators.
