This project demonstrates how to build, train, and evaluate a Convolutional Neural Network (CNN) for image classification using the CIFAR-10 dataset. The implementation leverages TensorFlow and Keras ...

train, and evaluate a fully connected neural network (Multi-Layer Perceptron, MLP) for image classification using the MNIST dataset. The implementation leverages TensorFlow and Keras to construct a ...

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

AI model crossNN identifies over 170 tumor types with high accuracy using genetic material, offering fast, non-invasive ...

DeepSeek recently released an updated version of its AI model, named R1-0528, which is designed for advanced reasoning like solving math problems and writing computer code. The model appears to ...

Subject headings represent the basic division of the Classification Plan. There are 16 subject headings based largely on function. Each subject heading has its own section in the Plan which includes a ...

Abstract: The effectiveness and robustness of medical image ... model to learn and represent complex features. These two modules enhance the robustness of the model and improves its generalization ...

Picking the right artificial intelligence and machine learning book depends on your current knowledge and what you want to ...

Google is offering free AI courses that can help professionals and students to upskill themselves. From introduction into ...