Composite-Intuitionistic-Fuzzy-C-Means-Algorithm MATLAB implementation for image segmentation experiments based on a fuzzy C-means style clustering framework. Overview This repository contains MATLAB ...
Data sharing is essential for advancing research in radiation oncology, particularly for training artificial intelligence (AI) models in medical imaging. However, privacy concerns necessitate ...
A new artificial intelligence (AI) tool could make it much easier-and cheaper-for doctors and researchers to train medical imaging software, even when only a small number of patient scans are ...
Pore space in tight sandstone formation is very complex with micro-scale and nano-scale pores/throats, the multi-scale characteristics needs to be considered for the construction of microscopic pore ...
A recent study published March 17 by researchers at the University of Michigan details the unique experiences of Black women on online dating platforms. Researchers examined the challenges Black women ...
BiRefNet C++ TENSORRT is designed to efficiently run bilateral reference segmentation tasks on the GPU. By harnessing TensorRT’s optimizations and CUDA kernels, it aims to deliver state-of-the-art ...
Abstract: C-means clustering algorithms have proven effective for image segmentation, but are limited by the following aspects: 1) the determination of a priori number of clusters. If the number of ...
Abstract: Fuzzy c-means algorithm with spatial constraints (FCM_S) is more effective for image segmentation. However, it still lacks enough robustness to noise and outliers, and costs much time in ...
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