CGFFCM: Cluster-weight and Group-local Feature-weight learning in Fuzzy C-Means clustering algorithm for color image segmentation
The fuzzy c-means (FCM) algorithm is a popular method for data clustering and image
segmentation. However, the main problem of this algorithm is that it is very sensitive to the …
segmentation. However, the main problem of this algorithm is that it is very sensitive to the …
Improved K-means clustering algorithm for big data mining under Hadoop parallel framework
W Lu - Journal of Grid Computing, 2020 - Springer
In order to improve the accuracy and efficiency of the clustering mining algorithm, this paper
focuses on the clustering mining algorithm for large data. Firstly, the traditional clustering …
focuses on the clustering mining algorithm for large data. Firstly, the traditional clustering …
Efficient superpixel-based brain MRI segmentation using multi-scale morphological gradient reconstruction and quantum clustering
Segmentation of brain MRI images is a fundamental task in medical image analysis.
However, existing clustering methods often face significant challenges, including high …
However, existing clustering methods often face significant challenges, including high …
Thermal error analysis and modeling for high-speed motorized spindles based on LSTM-CNN
Y Cheng, X Zhang, G Zhang, W Jiang, B Li - The International Journal of …, 2022 - Springer
The high-speed motorized spindle is the core part of high-precision machine tools, and its
performance governs the machining precision of machine tools. The thermal deformation …
performance governs the machining precision of machine tools. The thermal deformation …
[HTML][HTML] CGFFCM: A color image segmentation method based on cluster-weight and feature-weight learning
CGFFCM (Cluster-weight and Group-local Feature-weight learning in Fuzzy C-Means) is a
clustering-based color image segmentation approach. It applies an automatic cluster …
clustering-based color image segmentation approach. It applies an automatic cluster …
Research on data security detection algorithm in IoT based on K-means
The development of the Internet of Things has prominently expanded the perception of
human beings, but ensuing security issues have attracted people's attention. From the …
human beings, but ensuing security issues have attracted people's attention. From the …
Determination of pork meat storage time using near-infrared spectroscopy combined with fuzzy clustering algorithms
Q Li, X Wu, J Zheng, B Wu, H Jian, C Sun, Y Tang - Foods, 2022 - mdpi.com
The identification of pork meat quality is a significant issue in food safety. In this paper, a
novel strategy was proposed for identifying pork meat samples at different storage times via …
novel strategy was proposed for identifying pork meat samples at different storage times via …
Dynamic image segmentation and recognition measurement of axial compression experiment based on image clustering and semantic segmentation in RC column …
This paper introduces a dynamic image recognition and measurement method for
Reinforced Concrete (RC) Column with Fiber Reinforced Polymer (FRP) tubes axial …
Reinforced Concrete (RC) Column with Fiber Reinforced Polymer (FRP) tubes axial …
A Brain MRI Segmentation Method Using Feature Weighting and a Combination of Efficient Visual Features
Determining the area of brain tumors is an essential and fundamental step in automatic
diagnosis and treatment systems. The authors present a method based on a combination of …
diagnosis and treatment systems. The authors present a method based on a combination of …
[PDF][PDF] YOLO Based Deep Learning Model for Segmenting the Color Images
░ ABSTRACT-The first stage is to extract fine details from a picture using Red Green Blue
(RGB) colour space is colour image segmentation. Most grayscale and colour picture …
(RGB) colour space is colour image segmentation. Most grayscale and colour picture …