Master Market Segmentation for Enhanced Profitability and Growth

Discover how effective market segmentation identifies profitable customers and optimizes pricing, distribution, and product ...
IEEE

PCDAL: A Perturbation Consistency-Driven Active Learning Approach for Medical Image Segmentation and Classification

Abstract: In recent years, supervised learning using convolutional neural networks (CNN) has served as a benchmark for various medical image segmentation and classification. However, supervised ...
IEEE

ZSG-Net: A Zero-Shot Super-Resolution Guided Network for Ultrasound Image Segmentation and Classification

Abstract: Automated ultrasound (US) image analysis is hindered by challenges stemming from low resolution, noise, and non-uniform grayscale distribution, which compromise image quality. While many ...
Frontiers

Carotid plaque segmentation and classification using MRI-based plaque texture analysis and convolutional neural network

Background: Accurate segmentation and classification of carotid plaques are critical for assessing stroke risk. However, conventional methods are hindered by manual intervention, inter-observer ...
Frontiers

BrainTumNet: multi-task deep learning framework for brain tumor segmentation and classification using adaptive masked transformers

Background and objective: Accurate diagnosis of brain tumors significantly impacts patient prognosis and treatment planning. Traditional diagnostic methods primarily rely on clinicians’ subjective ...
Search Engine Land

Google updates image SEO best practices to say use the same image URL for same image across your pages

Google updated its Google image SEO best practices help document to recommend that you use the same image file name URL for the same image, even if you place that same image on different pages on your ...