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Found 5 papers, 0 papers with code
PELP: Pioneer Event Log Prediction Using Sequence-to-Sequence Neural Networks
Process mining, a data-driven approach for analyzing, visualizing, and improving business processes using event logs, has emerged as a powerful technique in the field of business process management.
NECA: Network-Embedded Deep Representation Learning for Categorical Data
We propose NECA, a deep representation learning method for categorical data.
Seed Stocking Via Multi-Task Learning
First, we will estimate the yield and risk of each variety as if they were planted at each location.
Co-occurrence Background Model with Superpixels for Robust Background Initialization
Background initialization is an important step in many high-level applications of video processing, ranging from video surveillance to video inpainting. However, this process is often affected by practical challenges such as illumination changes, background motion, camera jitter and intermittent movement, etc. In this paper, we develop a co-occurrence background model with superpixel segmentation for robust background initialization.
Simplex-Based 3D Spatio-Temporal Feature Description for Action Recognition
In addition, the results show that our SOD descriptor is a superior individual descriptor for action recognition.
