pharmaphorum

The patient segmentation model

Dividing patients into groups based on how they behave towards their condition can aid understanding of the issues that affect them and improve outcomes, such as quality of life in long-term ...
Unite.AI

AI-Generated Ad Images That Target Your Demographic – And, Eventually, You?

Advertisers aim to tailor ads to individual viewers to drive clicks, and while bespoke creatives for each person are currently impractical, new research suggests AI-generated imagery could soon be ...
Marketing

Coverage Patterns: Deciding Which and How Many Customer Segments to Target

At this point you must decide which and how many segments to target. To begin, consider various possible “coverage patterns.” These patterns are simply the ways a firm might choose and ultimately ...
GitHub

ControlNet: Adding Conditional Control to Text-to-Image Diffusion Models

All testing and development was conducted on 4x 16GB NVIDIA V100 GPUs 64-bit Python 3.8 and PyTorch 2.1 (or later). See https://pytorch.org for PyTorch install ...
IEEE

A Lightweight Semantic Segmentation Network Based on Self-Attention Mechanism and State Space Model for Efficient Urban Scene Segmentation

Abstract: In the semantic segmentation of remote sensing images, methods based on convolutional neural networks (CNNs) and Transformers have been extensively studied. Nevertheless, CNN struggles to ...
IEEE

Multi-Source Domain Adaptation for Medical Image Segmentation

Abstract: Unsupervised domain adaptation(UDA) aims to mitigate the performance drop of models tested on the target domain, due to the domain shift from the target to sources. Most UDA segmentation ...
GitHub

SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process

Mengyu Wang, Henghui Ding, Jun Hao Liew, Jiajun Liu, Yao Zhao, Yunchao Wei The trained models are provided in LR-SegRefiner and HR-SegRefiner. To assess SegRefiner on the COCO dataset, initiate the ...