Abstract: In this study, we explore the application of attention mechanisms to enhance deep learning models in the context of image classification. We assess several types of attention mechanisms ...

Overview A mix of beginner and advanced-level books to suit various learning needs.Each book blends theory with practical code examples for real-world applicati ...

Deep learning approaches, particularly convolutional neural networks (CNNs) and other architectures, were used in 49 papers. These models excel at image-based tasks such as land cover classification, ...

In today's data-driven environment, Python has become the mainstream language in the fields of machine learning and data science due to its concise syntax, rich library support, and active community, ...

White Blood Cell Classification is a deep learning project built with Python, TensorFlow, and Keras that classifies five types of WBCs from microscopic images using a CNN model. With advanced image ...

Abstract: With the rapid development of computer vision technology, image classification algorithm based on deep learning has become a hot research and application field. At present, the mainstream ...

Deep learning has been widely applied to high-dimensional hyperspectral image classification and has achieved significant improvements in classification accuracy. However, most current hyperspectral ...

Introduction: Breast cancer (BC) is a malignant neoplasm that originates in the mammary gland’s cellular structures and remains one of the most prevalent cancers among women, ranking second in ...

This project demonstrates how to build an image classification model using Convolutional Neural Networks (CNNs) to classify images into predefined categories. It covers data preprocessing, model ...