In order to improve the classification performance while reducing the labeling cost, this article presents an active deep learning approach for HSI classification, which integrates both active ...

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The project titled "Medical Image Classification for Disease Diagnosis Using Convolutional Neural Networks" aims to develop a robust and accurate machine learning model for the automatic ...

The results highlight the importance of incorporating cross entropy alongside traditional metrics for a more comprehensive evaluation of deep learning models in medical image classification, providing ...

A CNN is a deep learning model designed for the processing of grid-structured data, such as images or matrix data. In contrast to conventional neural networks, CNNs employ a specialized architecture ...

The proposed deep-learning algorithm detects three different diseases from features extracted from Optical Coherence Tomography (OCT) images. The deep-learning algorithm uses CNN to classify OCT ...

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 ...

Using CNN-FE, TL, and fine-tuning deep learning models as examples, this paper compares and analyzes deep learning algorithms for remote sensed image classification.