Abstract: Heart disease detection from medical images such as X-rays, CT scans, and MRIs is a critical task in the healthcare industry. In this proposed work, we explore the application of ...

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 ...

1 Faculty of Informatics, The University of Fukuchiyama, Kyoto, Japan. 2 School of Radiological Technology, Gunma Prefectural College of Health Sciences, Gunma, Japan. 3 School of Health Sciences, ...

1 Faculty of Information Systems and Computer Science, October 6 University, Giza, Egypt 2 Faculty of Computers and Artificial Intelligence, Information Technology Department, Matrouh University, ...

Artificial Intelligence (AI) and Machine Learning (ML) have become foundational technologies in the field of image processing. Traditionally, AI image recognition involved algorithmic techniques for ...

Purpose: To develop a visual function-based deep learning system (DLS) using fundus images to screen for visually impaired cataracts. Materials and methods: A total of 8,395 fundus images (5,245 ...

Abstract: Convolutional Neural Network (CNN) has made outstanding achievements in image processing and detection. The recent research uses CNN to classify the medical images, but this performance ...

Most computer vision algorithms use a convolution neural network, or CNN. Like basic feedforward neural networks, CNNs learn from inputs, adjusting their parameters to make a prediction. However, what ...