Local Standard Deviation Spectral Clustering

Xie, Juanying; Zhou, Ying; Ding, Lijuan

doi:10.1109/bigcomp.2018.00043

Cited by 12 publications

(5 citation statements)

References 19 publications

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“…When reading duplicate fles, since the index information has been added to the hash mapping object in memory at the frst reading, it is more efcient to query the index information directly from the hash map in memory at the second reading. In this section, three spectral clustering algorithms are analyzed experimentally, including traditional spectral clustering, Xie et al's [34] improved spectral clustering algorithm, and Zuo's improved spectral clustering algorithm. SEEDS dataset is selected from UCI data as experimental data.…”

Section: Read Speed Testmentioning

confidence: 99%

The Development Trend of China’s Agricultural Product Cold Chain Logistics from the Perspective of Big Data

Wang

2022

Advances in Multimedia

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With the gradual prosperity of social economy, people’s demand for agricultural products consumption has also gradually increased. Through the efficient introduction of big data technology, we can optimize and innovate the management system of agricultural cold chain logistics enterprises, realize the modernization of enterprise logistics management, and effectively improve the management efficiency of agricultural cold chain logistics enterprises. Using big data technology can improve the efficiency of information docking, improve the stickiness of enterprise customers, and speed up the value-added of cold chain logistics data. This study introduces the common clustering algorithms in the field of cold chain logistics, with emphasis on the spectral clustering algorithm. The spectral clustering algorithm not only reduces the error rate but also significantly reduces the time spent in the clustering process, which shows the effectiveness and feasibility of the application of spectral clustering algorithm in China’s agricultural cold chain logistics industry.

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Section: Read Speed Testmentioning

confidence: 99%

The Development Trend of China’s Agricultural Product Cold Chain Logistics from the Perspective of Big Data

Wang

2022

Advances in Multimedia

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“…Moreover, the parameter λ is not only a correction parameter but can also express the local details of the visible image. In order to improve the image contrast, we adopt the local standard deviation (LSD) [38] as the adaptive regularization parameter, which can be defined as follows:…”

Section: Fusion Of Base Componentsmentioning

confidence: 99%

“…To test the superiority and feasibility of the algorithms, we chose the comparison methods from the various aspects, such as the methods focused on the image transformation, the methods based on sparse representation or filtering methods, the deep learning methods and so on. The comparison methods in this paper mainly include curvelet transform (CVT) [40], complex wavelet transform (CWT) [41], guided filtering fusion (GFF) [38], gradient transform (GTF) [42], hybrid multi-scale decomposition fusion (HMSD) [43], Laplacian pyramid with sparse representation (LP_SR) [44], ratio pyramid (RP) [45], fusion based on median filtering (TSF) [46], the weighted least square optimization-based method (WLS) [47], anisotropic diffusion fusion (ADF) [48], U2fusion [26] and Densefuse [25]. The implementation of these compared methods is publicly available, the parameters of which are strictly in accord with the original papers.…”

Section: Experimental Settingmentioning

confidence: 99%

A Novel Saliency-Based Decomposition Strategy for Infrared and Visible Image Fusion

Bai

et al. 2023

Remote Sensing

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The image decomposition strategy that extracts salient features from the source image is crucial for image fusion. To this end, we proposed a novel saliency-based decomposition strategy for infrared and visible image fusion. In particular, the latent low-rank representation (LatLRR) and rolling guidance filter (RGF) are together employed to process source images, which is called DLatLRR_RGF. In this method, the source images are first decomposed to salient components and base components based on LatLRR, and the salient components are filtered by RGF. Then, the final base components can be calculated by the difference between the source image and the processed salient components. The fusion rule based on the nuclear-norm and modified spatial frequency is used to fuse the salient components. The base components are fused by the l2-energy minimization model. Finally, the fused image can be obtained by the fused base components and saliency detail components. Multiple groups of experiments on different pairs of infrared and visible images demonstrate that, compared with other state-of-the-art fusion algorithms, our proposed method possesses superior fusion performance from subjective and objective perspectives.

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“…Besides, ACE will adjust the contrast gain of the image into suitable value. The general equation [12] is defined as  …”

Section: Segmentation Using Local Standard Deviationmentioning

confidence: 99%

Shape and Level Bottles Detection Using Local Standard Deviation and Hough Transform

Rahman

Saad

Abdullah

2018

IJECE

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This paper presents shape and level analysis using local standard deviation and Hough transform technique to detect the shape and level of the bottle.A 155 sample images are used as a test product to detect shape and level. Local standard deviation is used contrast gain technique to segment the shape of the bottle by enhancing the contrast of the image. The ratio of the area is calculated from the extent parameter. The maximum and minimum water level is created by using Hough transform technique to identify the level of the water. Decision tree is applied to classify the shape and level of the bottle either good or defect condition. From experimental result, 97% and 93% accuracy of shape and level is achieved which shows that the proposed analysis technique is potential to be applied for beverages product inspection system.

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Local Standard Deviation Spectral Clustering

Cited by 12 publications

References 19 publications

The Development Trend of China’s Agricultural Product Cold Chain Logistics from the Perspective of Big Data

The Development Trend of China’s Agricultural Product Cold Chain Logistics from the Perspective of Big Data

A Novel Saliency-Based Decomposition Strategy for Infrared and Visible Image Fusion

Shape and Level Bottles Detection Using Local Standard Deviation and Hough Transform

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