Although it is critical to choose the right SaaS vendor and software package, the implementation of the delivery model is equally important to the overall project's success. Implementing the SaaS ...
Abstract: In the era of Industry 4, predictive maintenance (PdM) is a key feature for enabling the smart manufacturing paradigm. In this research, we proposed an enhanced variational autoencoder (VAE) ...
ABSTRACT: Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs when objects of different physical sizes appear identical in camera ...
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This repository contains the implementation, benchmarks, and supporting tools for my MSc dissertation project: Self-learning Variational Autoencoder for EEG Artifact Removal (Key code only). Benchmark ...
Recent advances in feature selection methods for breast cancer recurrence prediction: A systematic review. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...
Abstract: In this paper we present a new implementation of a Variational Autoencoder (VAE) for the calibration of sensors. We propose that the VAE can be used to calibrate sensor data by training the ...
Researched Variational Path Integral method as a team member of the Cyber Chem project group. Implemented one of the flavors of Quantum Monte Carlo method (Variational Path Integral simulation) on ...
├── data_pre/ # Data preprocessing modules │ ├── data_pre.py # Data preprocessing script │ └── dataset.py # Dataset class definition ├── dataset/ # Data directory │ ├── SRU_data.npy # Process data in ...
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