Well, they can. Models can be created that allow patients to self-segment in ways more accurate and relevant than ever before. The patient segmentation model discussed here divides the patient ...

Audience segmentation is the process of dividing viewers into groups based on shared characteristics, such as demographics, location, interests, and viewing behaviors. Video service providers use ...

As the landscape of digital marketing continues to grow and transform, innovation is no longer an option. It’s imperative.

This study developed CMF-ELSeg, a novel fully automatic multi-structure segmentation model based on deep ensemble learning. Methods: A total of 143 CMF computed tomography (CT) scans were ...

Abstract: Unsupervised domain adaptation for remote sensing semantic segmentation (UDA-RSSeg) is to adapt a model trained on the source-domain data to the target-domain samples, thereby minimizing the ...

Abstract: Domain shift is a significant challenge in medical image segmentation, primarily due to variations in image acquisition protocols, modalities, etc. Domain shift often causes models trained ...

The starting point for those studies is your customer-segmentation model. After you decide which approach to use to measure migration, the process is a virtuous circle of analyze, segment, campaign, ...

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image ...

CAST, groups fine details into object-level concepts as attention moves from lower to high layers, outputting a ...

Custom YOLOv8 model for detecting and classifying car body damage—optimized for fast inference and assistive use in inspection and service workflows like BMW pre-loaner inspections.