Analytics Insight

AI in Medical Imaging: Radiology, Pathology, and AI-Powered Scans

AI algorithms analyse complex medical images with speed and precision, supporting early disease detection.Radiology and ...
AZoOptics

Deep Learning in Optical Microscopy: Advancements and Applications

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.
Le Lézard

Chungnam National University Develops AI Model to Accelerate Defect-Based Material Design

Topological defects govern how many advanced materials behave, but predicting them has traditionally required slow, resource-intensive simulations. Researchers at Chungnam National University have ...
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, ...
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 ...
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 ...
Scientific Research Publishing

Tan, M. and Le, Q. (2019) EfficientNET: Rethinking Model Scaling for Convolution-al Neural Networks. International Conference on Machine Learning, Long Beach, 9-15 June 2019 ...

ABSTRACT: AI techniques are proving unbeatable in the fight for supremacy in methods of evaluation, optimization, control, object recognition, sensor monitoring, image interpretation, machine learning ...
IEEE

SVIFNN: Robust Inpainting Fourier Neural Network for SST Scientific Visualization Image Leveraging Significant Stability and Nonsignificant Anomalies

Abstract: The scientific visualization images (SVIs) of sea surface temperature (SST) play a pivotal role as visual resources for investigating oceanographic processes. However, they are often plagued ...
Frontiers

Transformer network enhanced by dual convolutional neural network and cross-attention for wheelset bearing fault diagnosis

Advances in deep learning methods have demonstrated remarkable progress in wheelset fault diagnosis. However, current deep neural networks suffer from design flaws, including low accuracy, high ...