Latest Articles for CNNs

Study uses advanced models to identify galaxy-galaxy strong lenses.

Researchers apply machine learning to better understand phase transitions in materials.

A look at methods used to predict increasing heatwave events.

A focus on trustworthiness in AI systems for reliable 6G communications.

A new model enhances land use mapping accuracy with limited data.

Discover the impact of Piecewise Linear Activations on deep learning models.

Research harnesses CNN technology to classify cell division stages in C. elegans and related species.

The Spatial Cross-scale Convolution Module improves efficiency in image recognition models.

This study explores using ear shapes for gender classification.

A new method enhances the robustness of Mixture of Experts CNNs against adversarial inputs.

This paper discusses how robots can identify conversation partners using visual cues.

A new method improves detection of environmental changes using remote sensing images.

Exploring new methods to enhance skin cancer diagnosis accuracy.

AMaizeD helps farmers spot maize diseases early using drone images.

SaEnet enhances CNN performance by focusing on essential features in images.

Learn how CNNs help clean up noisy images effectively.

This study evaluates the reliability of CNNs in brain MRI analysis.

This study presents methods for real-time pedestrian recognition using limited processing power.

RRAM technology improves convolutional neural networks' speed and efficiency.

A novel approach to improve security against harmful web traffic.

A new model enhances prediction accuracy for organelles in transmitted-light microscopy.

Innovative deep learning models enhance DDoS attack detection and response.

A new method improves image convolution without padding, enhancing quality and efficiency.

CATS v2 enhances accuracy in medical image segmentation through hybrid approaches.

New model SAMUS enhances ultrasound image segmentation for improved clinical accuracy.

A novel approach improves fMRI analysis for better brain disorder diagnosis.

This study reviews methods for improving predictive maintenance with sensor data analysis.

RingMo-lite improves remote sensing image analysis with efficiency and accuracy.

A novel method enhances cancer diagnosis by integrating weak causality signals in medical imaging.

This technique simplifies CAD model creation using just photographs.

New models enhance audio classification accuracy and resilience against noise and attacks.

Study reveals optimal network design for ECG analysis using CNNs.

Improving drone identification with RF signals and machine learning techniques.

DeepBEAS3D improves medical image segmentation through user interaction and deep learning.

Improved forecasting methods enhance power management and reliability.

ConvFormer enhances segmentation accuracy in medical imaging by combining CNNs and transformers.

Deep learning enhances accuracy in detecting colorectal cancer polyps.

NISF enhances anatomical shape segmentation in medical imaging with improved accuracy.

HEANA accelerates CNN tasks with improved speed and energy efficiency.

This study uses machine learning to forecast flame dynamics effectively.