ABSTRACT: Cloud detection is a critical preprocessing step in remote sensing image processing, as the presence of clouds significantly affects the accuracy of remote sensing data and limits its ...

Abstract: In the field of disease diagnosis where only a small dataset of medical images may be accessible, the light-weight convolutional neural network (CNN) has become popular because it can help ...

Light CNN v4 pretrained model is released. Download face dataset such as CASIA-WebFace, VGG-Face and MS-Celeb-1M. The MS-Celeb-1M clean list is uploaded: Baidu Yun, Google Drive. All face images are ...

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 ...

Autoencoder Anomaly Detection Using PyTorch Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are ...

This article explains how to use a PyTorch neural autoencoder to find anomalies in a dataset. A good way to see where this article is headed is to take a look at the screenshot of a demo program in ...