A DE-ANN Inspired Skin Cancer Detection Approach Using Fuzzy C-Means Clustering

Kumar, Manoj; Alshehri, Mohammed; AlGhamdi, Rayed; Sharma, Purushottam; Deep, Vikas

doi:10.1007/s11036-020-01550-2

Cited by 117 publications

(68 citation statements)

References 25 publications

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“…In the fourth step, a matrix norm is selected to compare the membership matrix before and after iteration ‖ U ( t +1) − U ( t ) ‖ ≤ ε . If the condition is not satisfied, return to the second step to continue the iteration [ 21 ]. Among them, the value of cluster number c needs to be set in advance.…”

Section: Fuzzy Clustering Generalized Regression Neural Network Evaluation Methodsmentioning

confidence: 99%

[Retracted] Evaluation of Teachers’ Educational Technology Ability Based on Fuzzy Clustering Generalized Regression Neural Network

Zhao

Guan

et al. 2021

Computational Intelligence and Neuroscience

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The improvement of teachers’ educational technology ability is one of the main methods to improve the management efficiency of colleges and universities in China, and the scientific evaluation of teachers’ ability is of great significance. In view of this, this study proposes an evaluation model of teachers’ educational technology ability based on the fuzzy clustering generalized regression neural network. Firstly, the comprehensive evaluation structure system of teachers’ educational technology ability is constructed, and then the prediction method of teachers’ ability based on fuzzy clustering algorithm is analysed. On this basis, the optimization prediction method of fuzzy clustering generalized regression neural network is proposed. Finally, the application effect of fuzzy clustering generalized regression neural network in the evaluation of teachers’ educational technology ability is analysed. The results show that the evaluation system of teachers’ educational technology ability proposed in this study is scientific and reasonable; fuzzy clustering generalized regression neural network model can better accurately predict the ability of teachers’ educational technology and can quickly realize global optimization. According to the fitness analysis results of the fuzzy clustering generalized regression neural network model, the model converges after the 20th iteration and the fitness value remains about 1.45. Therefore, the fuzzy clustering generalized regression neural network has stronger adaptability and has been optimized to a certain extent. The average evaluation accuracy of fuzzy clustering generalized regression neural network model is 98.44%, and the evaluation results of the model are better than other algorithms. It is hoped that this study can provide some reference value for the evaluation of teachers’ educational technology ability in colleges and universities in China.

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Section: Fuzzy Clustering Generalized Regression Neural Network Evaluation Methodsmentioning

confidence: 99%

[Retracted] Evaluation of Teachers’ Educational Technology Ability Based on Fuzzy Clustering Generalized Regression Neural Network

Zhao

Guan

et al. 2021

Computational Intelligence and Neuroscience

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“…It should be noted that while gating is effective against motion artifacts in PET imaging, the reduction of data used for reconstruction results in increased level of noise in images. Such noise could be mitigated using several post-processing approaches, such as deeplearning-based denoising methods [30] and fuzzy image processing methods [31][32][33].…”

Section: Applicability To Respiratory-gated Pet Studiesmentioning

confidence: 99%

A Respiratory Motion Estimation Method Based on Inertial Measurement Units for Gated Positron Emission Tomography

Lehtonen

Teuho

Koskinen

et al. 2021

Sensors

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We present a novel method for estimating respiratory motion using inertial measurement units (IMUs) based on microelectromechanical systems (MEMS) technology. As an application of the method we consider the amplitude gating of positron emission tomography (PET) imaging, and compare the method against a clinically used respiration motion estimation technique. The presented method can be used to detect respiratory cycles and estimate their lengths with state-of-the-art accuracy when compared to other IMU-based methods, and is the first based on commercial MEMS devices, which can estimate quantitatively both the magnitude and the phase of respiratory motion from the abdomen and chest regions. For the considered test group consisting of eight subjects with acute myocardial infarction, our method achieved the absolute breathing rate error per minute of 0.44 ± 0.23 1/min, and the absolute amplitude error of 0.24 ± 0.09 cm, when compared to the clinically used respiratory motion estimation technique. The presented method could be used to simplify the logistics related to respiratory motion estimation in PET imaging studies, and also to enable multi-position motion measurements for advanced organ motion estimation.

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“…2) The CSP determines the original file F i and its corresponding tag , ij  , which will verify the formula (5) in the TagGen algorithm. Based on the nature of bilinear map, it can be derived to obtain the results prove that it is correct: .…”

Section: Security Analysismentioning

confidence: 99%

“…There are two hidden dangers in this way. One is the lack of control over the confidentiality and integrity of the data and the other is that it is difficult to recover the data if the local copy is deleted [4][5][6]. In order to solve these problems, the researchers proposed that users can encrypt data before outsourcing and sending it to a remote cloud server [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Integrity Auditing for Multi-Copy in Cloud Storage Based on Red-Black Tree

Liu

Xian-wei

et al. 2021

IEEE Access

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With the rapid development of cloud storage, cloud users are willing to store data in the cloud storage system, and at the same time, the requirements for the security, integrity, and availability of data storage are getting higher and higher. Although many cloud audit schemes have been proposed, the data storage overhead is too large and the data cannot be dynamically updated efficiently when most of the schemes are in use. In order to solve these problems, a cloud audit scheme for multi-copy dynamic data integrity based on red-black tree full nodes is proposed. This scheme uses ID-based key authentication, and improves the classic Merkel hash tree MHT to achieve multi-copy storage and dynamic data manipulation, which improves the efficiency of real-time dynamic data update (insertion, deletion, modification). The third-party audit organization replaces users to verify the integrity of data stored on remote cloud servers, which reduces the computing overhead and system communication overhead. The security analysis proves that the security model based on the CDH problem and the DL problem is safe. Judging from the results of the simulation experiment, the scheme is safe and efficient.

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A DE-ANN Inspired Skin Cancer Detection Approach Using Fuzzy C-Means Clustering

Cited by 117 publications

References 25 publications

[Retracted] Evaluation of Teachers’ Educational Technology Ability Based on Fuzzy Clustering Generalized Regression Neural Network

[Retracted] Evaluation of Teachers’ Educational Technology Ability Based on Fuzzy Clustering Generalized Regression Neural Network

A Respiratory Motion Estimation Method Based on Inertial Measurement Units for Gated Positron Emission Tomography

Integrity Auditing for Multi-Copy in Cloud Storage Based on Red-Black Tree

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