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 ...

In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept ...

Abstract: Computer network attacks have undergone rapid evolution over the past few years. As a result, current signature – based intrusion detection system (IDS) anomaly detection has struggled to ...

The bipedal wheel-legged robot combines the high energy efficiency of wheeled movement with the terrain adaptability of legged locomotion. However, achieving a smooth transition between these two ...

A Democrat won a state legislative special election in a district that President Trump carried by 17 percentage points, unnerving Republicans in Texas and beyond. By J. David Goodman Reporting from ...

Deep Learning (DL) has emerged as a transformative approach in artificial intelligence, demonstrating remarkable capabilities in solving complex problems once considered unattainable. Its ability to ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...