Researchers at the Department of Energy's Oak Ridge National Laboratory have developed a deep learning algorithm that ...

Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results. In ...

Abstract: Convolutional Neural Networks (CNNs) dominate medical image classification, yet their “black box” nature limits understanding of their decision-making process. This study applies ...

Sign up for the Slatest to get the most insightful analysis, criticism, and advice out there, delivered to your inbox daily. By mid-October, the Democrats’ chances ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Recently, there has been a lot of hullabaloo about the idea that large reasoning models (LRM) are unable to think. This is mostly due to a research article published by Apple, "The Illusion of ...

Nitika Garg does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their ...

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.