Scientific Research Publishing

Research on Structural Damage Identification Method Based on Convolutional Neural Network ()

1 College of Finance and Commerce, Guangzhou Railway Polytechnic, Guangzhou, China. 2 School of Intelligent Construction and Civil Engineering, Zhongyuan University of Technology, Zhengzhou, China. 3 ...
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, ...
IEEE

Enhancing Interpretability of Deep Canonically Correlated Autoencoders Through Convolutional Neural Networks and Visualization

Abstract: In this study, we studied unsupervised multiview learning techniques focused on maximizing correlation, particularly Deep Canonically Correlated Autoencoders (DCCAE). The goal of this study ...
pv magazine International

PV module fault diagnosis uses convolutional neural network

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...
SDxCentral

Extreme Networks launches agentic AI networking platform

Extreme Networks has fully launched its Extreme Platform One, an agentic AI-focused network visualization offering. Revealed back in February, the platform is now generally available, with the vendor ...
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, ...
GitHub

ElvianElvy/Graph-Convolutional-LSTM-Spatial-Temporal-GNN-

A comprehensive PyTorch-based system for predicting cryptocurrency prices using a state-of-the-art Spatial-Temporal Graph Neural Network (ST-GNN) model. This advanced implementation integrates ...