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 ...

The prospect of Paramount’s buying Warner Bros. Discovery had led CNN journalists to wonder if the channel may be combined with CBS News. Instead, CNN will remain in a separate corporate entity. By ...

The cnn.py implemented a simple CNN with pytorch. The network consists of two convolutional-ReLU-pooling layer and a fully-connected-softmax layer. The network structure is as following: ...

Gradient Descent: This article describes how to implement a gradient descent using the differential approach (2D example implementation), then, using the perturbation approach (3D example ...

A PyTorch implementation of the CVPR 2018 paper Domain Adaptive Faster R-CNN for Object Detection in the Wild. The original code used by the authors can be found here. This implementation is built on ...

This project is a binary classification problem of audio data that aims to classify human voices from audio recordings. This project uses a feed forward neural network and a convolutional neural ...

A real-time facial emotion recognition web app using a custom-trained CNN on the FER-2013 dataset. Built with Flask, OpenCV, and PyTorch.