Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

Abstract: Unsupervised domain adaption (UDA), which aims to enhance the segmentation performance of deep models on unlabeled data, has recently drawn much attention. In this paper, we propose a novel ...

1.2.2 Installing CUDA 11.3 1.2.3 Installing gcc 10 and linking to CUDA 11.3 ...

This study aims to investigate the application of visual information processing mechanisms in the segmentation of stem cell (SC) images. The cognitive principles underlying visual information ...

Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...

Crop segmentation, the process of identifying crop regions in images, is fundamental to agricultural monitoring tasks such as yield prediction, pest detection, and growth assessment. Traditional ...

ABSTRACT: Doping is an issue associated with elite sports as athletes attempt to enhance their performance to gain an edge over other athletes. However, the prevalence of doping is continuously ...

Abstract: This paper proposes a new approach to the feature based unsupervised image segmentation. The difficulty with the conventional unsupervised segmentation lies in finding appropriate features ...