Key to human intelligence lies in how brain networks work together, neuroimaging study suggests

Modern neuroscience understands the brain as a set of specialized systems. Aspects of brain function such as attention, ...
Opinion
SpaceNewsOpinion

We need a ‘Planetary Neural Network’ for AI-enabled space infrastructure protection

For example, a Convolutional Neural Network (CNN) trained on thousands of radar echoes can recognize the unique spatial signature of a small metallic fragment, even when its signal is partially masked ...

An A.I. Pioneer Warns the Tech ‘Herd’ Is Marching Into a Dead End

Yann LeCun helped create the technology behind today’s chatbots. Now he says many tech companies are on the wrong path to ...
Devdiscourse

AI-driven rainfall forecasting shows major gains in predicting flood-triggering storms

Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...
GitHub

Tanishk190/Eurusd-lstm-predictor

A machine learning web application that predicts the next day's closing price for the EUR/USD currency pair using historical data and LSTM neural networks. ML-Project/ ├── app.py # Flask web ...
Frontiers

Multi-field numerical model and LSTM-based neural networks for thermal field predictions of concrete-filled steel tubes

1 Construction Branch of State Gird Jiangsu Electric Power Co. Ltd, Nanjing, China 2 Civil Engineering School, Southeast University, Nanjing, China Concrete-filled steel tube (CFST) columns are widely ...
Frontiers

Modeling ring current proton distribution using MLP, CNN, LSTM, and transformer networks

This study aims at developing ring current proton flux models using four neural network architectures: a multilayer perceptron (MLP), a convolutional neural network (CNN), a long short-term memory ...
Scientific Research Publishing

Priyadarshini, I. and Cotton, C. (2021) A Novel LSTM-CNN-Grid Search-Based Deep Neural Network for Sentiment Analysis.

ABSTRACT: In today’s digital background, sentiment analysis has become an essential factor of Natural Language Processing (NLP), offering valuable insights from vast online data sources. This paper ...
IEEE

An LSTM Network With Neural Plasticity for Driver Fatigue Recognition on Real Roads

Abstract: Driver fatigue recognition is a highly challenging issue because of the complexity of road conditions, the dynamics of traffic flow, and the differences between drivers. This article ...
IEEE

Long Short-Term Memory Neural Network Combined With a Hybrid-Modular Clockwork Structure for Transient Modeling of Nonlinear Circuits

Abstract: This paper presents a novel macromodeling method and neural network structure called Clockwork Long Short-Term Memory (CWLSTM), tailored for high-speed nonlinear circuits. The proposed ...