Analytics Insight

Best Deep Learning Books to Read in 2026

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

AI sheds light on hard-to-study ocean currents

The Indonesian Throughflow carries both warm water and fresh water from the Pacific into the Indian Ocean. As the only ...
Deep Learning with Yacine on MSNOpinion

Local response normalization (LRN) in deep learning – simplified!

Understand Local Response Normalization (LRN) in deep learning: what it is, why it was introduced, and how it works in ...
Hosted on MSN

Network in Network (NiN) Explained – Deep Neural Network Tutorial with PyTorch

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
Frontiers

Convolutional neural networks decode finger movements in motor sequence learning from MEG data

1 Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia 2 Department of Learning, Data Analytics and Technology, Section Cognition, Data and ...
C&EN

Interpretable Multiscale Convolutional Neural Network for Classification and Feature Visualization of Weak Raman Spectra of Biomolecules at Cell Membranes

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Raman spectroscopy in biological applications faces challenges due to complex spectra, ...
Scientific Research Publishing

Advanced Skin Disease Diagnosis and Treatment: Leveraging Convolutional Neural Networks for Image-Based Prediction and Comprehensive Health Assistance ()

Skin conditions are a worldwide health issue that requires prompt and accurate diagnosis in order to be effectively treated. This study presents a Convolutional Neural Network (CNN)-based automated ...
IEEE

Convolutional Neural Networks Demystified: A Matched Filtering Perspective-Based Tutorial

Abstract: Deep neural networks (DNNs) and especially convolutional neural networks (CNNs) have revolutionized the way we approach the analysis of large quantities of data. However, the largely ad hoc ...