The chemical's classification is "based on the presumption of the chemical being carcinogenic, mutagenic, or reprotoxic based ...

What if plants could speak when they were thirsty? Agriculture, in essence, is a dialog among crops, soil and climate. Yet ...

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 ...

🧠 Image-Classification-using-CNN This repository contains a Jupyter notebook that implements a Convolutional Neural Network (CNN) for image classification using TensorFlow and Keras. The project ...

This assignment investigates the usage of (CNN) and synthetic neural networks (ANN) for picture classification. We compare the overall performance of these strategies for my part and together to ...

As a new optical machine learning framework, the diffractive deep neural network (D2NN) has attracted much attention due to its advantages such as low power consumption, parallel computing, and fast ...

This project demonstrates image classification using a Convolutional Neural Network (CNN) on the CIFAR-10 dataset. The model is trained to classify images into one of 10 classes.

This study reviews the utilization of Convolutional Neural Networks (CNN) to classify satellite images into three distinct groups. This technique can classify three distinct classes in addition to ...