This is a deep learning-based project for plant leaf disease recognition, which aims to automatically identify the health status and specific disease types of plant leaves using convolutional neural ...

Deep learning algorithms for ultra-widefield fundus photos can identify retinal detachments with precision, supporting early diagnoses in varied settings. Deep learning (DL) models applied to ...

However, previous studies did not systematically synthesize their diagnostic accuracy. Objective: To quantitatively explore the diagnostic efficacy of deep learning (DL) and radiomics for extracranial ...

Abstract: Opinions for any product, topic or organization are provided by users on Social networking and E-commerce sites. These opinions have high influence on other users’ purchasing decisions.

Artificial intelligence (AI)-based models and algorithms may aid in achieving overall more efficient and accurate diagnostics in various medical specialties. Such AI-based tools could be integrated ...

Deep Learning Crash Course: A Hands-On, Project-Based Introduction to Artificial Intelligence is written by Giovanni Volpe, Benjamin Midtvedt, Jesús Pineda, Henrik Klein Moberg, Harshith Bachimanchi, ...

This project uses deep learning techniques to detect malware by analyzing file characteristics, byte sequences, and behavioral patterns. It employs Convolutional Neural Networks (CNNs) for image-based ...

Liver cancer, including hepatocellular carcinoma (HCC), is a leading cause of cancer-related deaths globally, emphasizing the need for accurate and early detection methods. LiverCompactNet classifies ...