IMAGE SEGMENTATION AND OBJECT SELECTION BASED ON MULTI-THRESHOLD PROCESSING by Vladimir Yu. Volkov, Oleg A. Markelov, Mikhail I. Bogachev

“…The development of a methodology based on multi-threshold analysis. Materials and methods. The developed image segmentation and object selection approach having optimal selection threshold assessment is based on the results of multi-threshold image analysis. …”
Get full text

Smart fiber with overprinted patterns to function as chip-like multi-threshold logic switch circuit by Xiaofei Wei, Rui Li, Siwei Xiang, Long Qin, Xinxin Luo, Jie Xue, Xing Fan

“…For which, each network node executes not only multi-physiological sensing, but also in-situ logic computing to save cloud computing power for massive data analysis. Herein, we present a smart fiber with multilayers of overprinted patterns, composed of many small units with 0.3 mm long to function as a one-dimension (1D) array of chip-like multi-threshold logic-switch circuit. …”
Get full text

Multi-Threshold Remote Sensing Image Segmentation Based on Improved Black-Winged Kite Algorithm by Yi Zhang, Xinyu Liu, Wei Sun, Tianshu You, Xin Qi

“…Experimental validation using representative samples from the ISPRS Potsdam benchmark dataset demonstrates that our IBKA-optimized OTSU multi-threshold segmentation method outperforms traditional IBKA-optimized pulse coupled neural network (PCNN) approaches in remote sensing image analysis. …”
Get full text

Multiscale pore/throat characterization in tight sandstone formation with multi-threshold image segmentation algorithm by Hu Rongrong, Han Jiangchen, Wang Chenchen, Zhu Jian, Dong Hu

“…IntroductionPore 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 model accurately.MethodsIn this paper, micro-CT is used to obtain the representative 3D micro-scale gray image, and nano-CT is used to obtain the representative 3D nano-scale gray image based on the representative nano subsample. Then, the multi-threshold image segmentation algorithm is introduced to segment the micro-scale and nano-scale gray image respectively. …”
Get full text

An Improved Multi-Threshold Clutter Filtering Algorithm for W-Band Cloud Radar Based on K-Means Clustering by Zhao Shi, Lingjiang Huang, Fengyuan Wu, Yong Lei, Huiying Wang, Zhiya Tang

“…The clutter-filtered data were further used for the verification analysis of cloud and fog identification. The results demonstrate that the proposed multi-threshold method effectively removes clutter and significantly reduces its impact on cloud and fog echo under weather conditions of clouds, fog, and coexisting cloud–fog, while controlling the loss of cloud and fog echo within the required accuracy range.…”
Get full text

Express Method of Analysis Morphological Parameters of Graphene Coatings on a Copper Substrate by V.S. Levitskiy, T.S. Koltsova, M.V. Kozlova, T.V. Larionova, V.O. Sobol

Get full text

Optimal performance design of bat algorithm: An adaptive multi‐stage structure by Helong Yu, Jiuman Song, Chengcheng Chen, Ali Asghar Heidari, Yuntao Ma, Huiling Chen, Yudong Zhang

“…AMSBA was also applied to the multi‐threshold image segmentation of Citrus Macular disease, which is a bacterial infection that causes lesions on citrus trees. …”
Get full text

Early Detection of Pine Wilt Disease by Combining Pigment and Moisture Content Indices Using UAV-Based Hyperspectral Imagery by Rui Hou, Biyao Zhang, Guofei Fang, Sihan Yang, Lei Guo, Wenjiang Huang, Jing Yao, Quanjun Jiao, Hong Sun, Jiayu Yan

“…The optimal canopy pigment index (CI) and canopy moisture content index (WASCOSBNDI) were then chosen through significance testing and derivative analysis. Based on the asynchronous variations in canopy moisture and pigment content during the development of PWD, the CI, WASCOSBNDI, and CI-WASCOSBNDI models were developed using a multi-threshold segmentation method to identify trees at different stages of infection. …”
Get full text

In-depth analysis of the risk factors for persistent severe acute respiratory syndrome coronavirus 2 infection and construction of predictive models: an exploratory research study by Jia Zhang, Weihua Zhu, Piping Jiang, Feng Ma, Yulin Li, Yuwei Cao, Jiaxin Li, Zhe Zhang, Xin Zhang, Wailong Zou, Jichao Chen

“…This study integrated multi-threshold analysis (14/20/30 days), whole-genome sequencing, and machine learning to investigate diagnostic thresholds for persistent SARS-CoV-2 infection and developed a generalizable risk prediction model. …”
Get full text

Progressive noise photons removal from ICESAT-2 data based on the characteristics of different types of noise by Zhenyang Hui, Li Zhang, Shuanggen Jin, Wenbo Chen, Penggen Cheng, Yao Yevenyo Ziggah

“…Specifically, isolated noise photons are automatically identified using a multi-thresholding strategy based on the maximum between-clustering variance algorithm without requiring parameter tuning. …”
Get full text

A control-driven transition strategy for enhanced multi-level threshold image segmentation optimization by Laith Abualigah, Mohammad H. Almomani, Saleh Ali Alomari, Raed Abu Zitar, Vaclav Snasel, Kashif Saleem, Aseel Smerat, Absalom E. Ezugwu

“…This work proposes an image segmentation approach based on a multi-threshold segmentation method and the enhanced Flood Algorithm combined with the Non-Monopolize search (named Improved IFLANO). …”
Get full text

A new BWO-based RGB vegetation index and ensemble learning strategy for the pests and diseases monitoring of CCB trees using unmanned aerial vehicle by Keliang Hu, Keliang Hu, Junchen Liu, Hai Xiao, Qiangguo Zeng, Jun Liu, Jun Liu, Lei Zhang, Lei Zhang, Man Li, Man Li, Zhihui Wang, Zhihui Wang

“…To account for the collinearity relationship between indices, the random forest variable importance and correlation coefficient iterative analysis algorithm are employed to select indices, retaining the most important or lowest collinearity multiple vegetation indices. …”
Get full text