Smithsonian Magazine

Computers Are Getting Much Better at Image Recognition

The machine-learning programs that underpin their ability to “see” still have blind spots—but not for much longer ...
Deep Learning with Yacine on MSN

Inception Net V1 Explained: Step-by-Step PyTorch Implementation

Learn how the Inception Net V1 architecture works and how to implement it from scratch using PyTorch. Perfect for deep ...
Superbike News

Neural networks: how they work and where they are used

Neural networks are algorithmic systems created based on the principle of the human nervous system. They consist of many ...
IEEE

Design of a Low-Power Analog Integrated Deep Convolutional Neural Network

Abstract: In this article, a framework for the analog implementation of a deep convolutional neural network (CNN) is introduced and used to derive a new circuit architecture which is composed of an ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ...
C&EN

Neural Network Prediction of Micrometer-Scale Equivalent Contact Angle Mapping: From Microforce Measurements to Local Wettability Characterization

State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China ...
Hosted on MSN

Highway Networks – Deep Neural Network Explained

Explore Highway Networks, a neural network architecture designed to improve training of deep networks. Concepts and examples explained. #HighwayNetworks #DeepLearning #NeuralNetworks Democrats Launch ...
IEEE

Attention-Based Convolutional Neural Network Model for Skin Cancer Classification

Abstract: Early detection of skin cancer (SC) is paramount for effective treatment. Although convolutional neural networks (CNN) have facilitated automated learning of high-level features from ...