Automated image colorization might be the most dramatic AI enhancement feature in visual effects. It predicts the original colors that should be present based on black-and-white images, resulting in ...

State Key Laboratory of Integrated Service Networks, Xidian University, Xian 710071, China State Key Discipline Laboratory of Wide Bandgap Semiconductor Technology School of Microelectronics, Xidian ...

This project implements a system for detecting anomalies in time series data collected from Prometheus. It uses an LSTM (Long Short-Term Memory) autoencoder model built with TensorFlow/Keras to learn ...

This is a Python repository for recovering weights or re-training a multimodal masked autoencoder on anatomical brain MRIs. It naturally handles missing modalities and processes any combination of ...

Anomaly detection is a typical binary classification problem under the condition of unbalanced samples, which has been widely used in various fields of data mining. For example, it can help detect ...

Background: Early detection is clinically crucial for the strategic handling of sarcopenia, yet the screening process, which includes assessments of muscle mass, strength, and function, remains ...

Abstract: As the number of heterogenous IP-connected devices and traffic volume increase, so does the potential for security breaches. The undetected exploitation of these breaches can bring severe ...

The precise segmentation of the optic cup (OC) and the optic disc (OD) is important for glaucoma screening. In recent years, medical image segmentation based on convolutional neural networks (CNN) has ...

Abstract: Parkinson's Disease (PD) diagnosis is a challenging task for doctors because of the non-availability of separate testing and prediction methodology. PD is identified through various clinical ...