Latest Articles for Machine Learning

A machine learning approach enhances detection of defects in biological tissues.

This article presents a novel similarity measure for neural network representations using contrastive learning.

This article discusses F-theory's role in unifying fundamental forces and analyzing particle behavior.

A new approach to improve image quality and compression efficiency.

Using raw radar data enhances object detection in autonomous systems.

A new method enhances the training of Feedforward Neural Networks through smart heuristic selection.

A new method enhances sound recognition across diverse smart devices.

Explore MaMMUT's innovative model for integrating images and text seamlessly.

Exploring the limits of AI models in understanding and applying textual entailment.

A novel method reduces labeling cost in image segmentation using superpixels.

This article examines techniques for assessing spatial data model performance.

A new approach enhances image search through sketches using Semantic Anchors.

VideoMAE V2 enhances video model training with dual masking and larger datasets.

Introducing a new method for improved local feature matching using geometric insights.

A new method enhances the detection and tracking of moving objects in multi-camera systems.

A novel approach to enhance accuracy in matching local features across images.

Effective workload prediction using advanced GRU neural networks for resource management.

Examining how long-tail distribution affects deep neural networks and their performance.

This work creates high-quality images of words in various handwriting styles.

A look at precision matrix estimation methods, focusing on Local Linear Approximation and sparsity.

A new framework enhances trajectory prediction accuracy for complex movements.

New methods enhance MRI image quality from incomplete data using dual-domain approaches.

Exploring self-supervised learning methods for efficient point cloud processing.

A novel approach using quantum computing for improved data classification.

Using importance sampling can enhance neural network training efficiency and performance.

Examining how different methods influence predictions in ontology-based machine learning.

A new framework merges deep learning and clustering for better bone analysis.

Learn how SNNs replicate brain processes for efficient computing.

A new method improves robot learning with few demonstrations.

This article examines how loss functions affect machine learning model performance.

A framework to guide pre-training decisions for graph neural networks.

This study evaluates language models using newly created datasets for negation and role reversal.

A look at how function complexity affects model performance.

A new tool streamlining 3D CNN model deployment on FPGA devices.

This study assesses VAE performance in biological imaging using cryo-electron microscopy.

A new method enables better image generation from layouts, enhancing object control.

A new method enhances MAE for better visual understanding.

A guide to tuning parameters in SVMs and boosted trees for better accuracy.

This article discusses methods for helping robots understand object uses and interactions.

Using federated learning to predict emojis across languages while ensuring data privacy.