A new technical paper titled “Domain Adaptation for Image Classification of Defects in Semiconductor Manufacturing” was ...

We propose a convolutional autoencoder neural network for image classification in YCbCr color space to reduce computational complexity. We first learned local image features from image patches in ...

Emotion recognition is of great importance for human-computer interaction. Emotion recognition technology based on physiological signals has shown great potential because of its strong objectivity and ...

Convolutional Neural Network (CNN) for image classification on the CIFAR-10 dataset using TensorFlow and Keras. Includes data augmentation, L2 regularization, and detailed evaluation with ...

Pytorch implementation for image compression and reconstruction via autoencoder. This is an autoencoder with cylic loss and coding parsing loss for image compression and reconstruction. Network ...