The dilated convolution algorithm, which is widely used for image segmentation, is applied in the image classification field in this paper. In many traditional image classification algorithms, ...

Document image classification has a significant difficulty for the retrieval of digital documents and systems management in recent years. The main goal of this study is to investigate the ...

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 ...

• Developed Convolutional Neural Network (CNN) models for an image classification task, working with a dataset of 13,394 images across 10 classes. • Implemented data augmentation, transfer learning, ...

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 ...

The Project utilizes Convolutional Neural Networks (CNNs) to classify facial expressions. using jupyter notebook showing how to build an image classifier with Python and Tensorflow - MAmr9UH/CNN-Im ...

This study presents a deep Convolutional Neural Network (CNN) model for automated COVID-19 RATD image classification. Methods: To address the absence of a RATD image dataset, we crowdsourced 900 ...