In this tutorial, we explore how we can decode linguistic features directly from brain signals using a modern neuroAI pipeline. We work with MEG data and build an end-to-end system that transforms raw ...

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 ...

Social media companies are under pressure to crack down on so-called deepfake videos that use deceptive images of real people. By Natallie Rocha Reporting from San Francisco See more of our coverage ...

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 ...

As a driving force of the Fourth Industrial Revolution, deep learning methods have achieved significant success across various fields, including genetic and genomic studies. While individual-level ...

5,572 SMS messages. 747 spam. Can a custom neural network compete with BERT? This project compares three deep learning approaches to SMS spam detection: a custom LSTM architecture built from scratch, ...

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, ...

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 ...

Abstract: Anything that is connected to the internet is vulnerable, for example mobile phones, personal laptops, tablets, routers, and smart speakers. Cybercriminals need one point of weakness like ...