This is a pytorch implementation of the Muti-task Learning using CNN + AutoEncoder. Cifar10 is available for the datas et by default. You can also use your own dataset. epoch,train loss,train accuracy ...

Abstract: Medical image classification has significantly advanced due to deep learning techniques, however, the performance remains limited by class imbalance and the nature distribution of healthcare ...

Abstract: Traditional approaches to anomaly detection are often limited and less effective in dealing with new and unknown threats, including DDoS attacks. Distributed denial-of-service (DDoS) attacks ...

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

If you’ve ever finished an online lecture and realized you barely remember what was covered, you’ve experienced the difference between active vs. passive learning. In virtual classrooms, it’s easy to ...

To get an inside look at the heart, cardiologists often use electrocardiograms (ECGs) to trace its electrical activity and magnetic resonance images (MRIs) to map its structure. Because the two types ...

Department of Chemistry, Zhongshan Hospital, Fudan University, Shanghai 200000, China Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200092 ...

ABSTRACT: This work presents an innovative Intrusion Detection System (IDS) for Edge-IoT environments, based on an unsupervised architecture combining LSTM networks and Autoencoders. Deployed on ...

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...