To address growing demands for efficient AI computing, scientists in China developed a reconfigurable integrated photonic chip that supports diverse neural network models within a unified hardware ...

Inspired by these developments, we propose a novel hyperspectral image classification method that integrates CNN and Transformer architectures. The method first employs 3D and 2D convolution ...

Training a Large CNN for Image Classification: Researchers developed a large CNN to classify 1.2 million high-resolution images from the ImageNet LSVRC-2010 contest, spanning 1,000 categories. The ...

Matsuyama, E. , Watanabe, H. and Takahashi, N. (2024) Performance Comparison of Vision Transformer- and CNN-Based Image Classification Using Cross Entropy: A Preliminary Application to Lung Cancer ...

This project focuses on building and training a Convolutional Neural Network (CNN) for image classification using the MNIST dataset. The MNIST dataset consists of 70,000 grayscale images of ...

Convolutional neural network structures based on deep learning are employed for image classification of the MNIST dataset. The study aims to tackle the model overfit issue, using two different ...

Dr. James McCaffrey of Microsoft Research details the 'Hello World' of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset.