Language shapes visual processing in both human brains and AI models, study finds

Neuroscientists have been trying to understand how the brain processes visual information for over a century. The development of computational models inspired by the brain's layered organization, also ...
IEEE

AirQuaNet: A Convolutional Neural Network Model With Multi-Scale Feature Learning and Attention Mechanisms for Air Quality-Based Health Impact Prediction

Abstract: Air pollution is a vital environmental and public health issue responsible for millions of early deaths worldwide every year. Predicting air quality and associated health impacts is crucial ...
GitHub

ResNet-50 Image Classification

This project implements ResNet-50, a deep convolutional neural network with 50 layers that uses residual connections to enable training of very deep networks. The architecture includes identity ...
IEEE

IntegralCAM: Integral-based contribution estimation and visualization for convolutional neural networks

To explain how a convolutional neural network (CNN) processes an image, it is common to generate classification activation maps (CAMs) to reveal image areas that are relevant to output. Nevertheless, ...
WealthManagement.com

BNY Pershing Launches Advisor Growth Network, New Wove Features

BNY Pershing has launched a financial advisor growth network intended to support breakaways in going independent. The Advisor Growth Network, or AGN, is one of the announcements coming out of BNY ...
Frontiers

An abnormal traffic detection method for chain information management system network based on convolutional neural network

Chain information management system is widely used, providing convenience for the operation and management of enterprises. However, the problem of abnormal network traffic becomes increasingly ...
Frontiers

Fault diagnosis algorithm based on multi-channel neighbor feature convolutional network

Introduction: The health status of bearings is an essential prerequisite to ensure the safe and stable operation of vehicles. However, the negative impact of covariate shifts among data channels on ...
Scientific Research Publishing

Liu, Y., Pu, H. and Sun, D. (2021) Efficient Extraction of Deep Image Features Using Convolutional Neural Network (CNN) for Applications in Detecting and Analysing Complex Food ...

ABSTRACT: The food recognition systems are available for foreign dishes but much work has not been done for our traditional dishes making it difficult to classify the traditional dishes and the ...