2021
DOI: 10.1155/2021/6168562
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[Retracted] Application of CNN Algorithm Based on Chaotic Recursive Diagonal Model in Medical Image Processing

Abstract: With the gradual improvement of people’s living standards, the production and drinking of all kinds of food is increasing. People’s disease rate has increased compared with before, which leads to the increasing number of medical image processing. Traditional technology cannot meet most of the needs of medicine. At present, convolutional neural network (CNN) algorithm using chaotic recursive diagonal model has great advantages in medical image processing and has become an indispensable part of most hospitals. T… Show more

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Cited by 9 publications
(6 citation statements)
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References 16 publications
(11 reference statements)
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“…This shows that LSTM has obvious advantages over traditional shallow networks in the problem of passenger flow prediction. Passenger flow prediction can be regarded as a time series prediction problem, and LSTM can obtain the long‐term dependency information of the data and has good performance in solving the time series prediction problem [33]. However, LSTM also has certain drawbacks, such as computational complexity, and can only handle time series.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…This shows that LSTM has obvious advantages over traditional shallow networks in the problem of passenger flow prediction. Passenger flow prediction can be regarded as a time series prediction problem, and LSTM can obtain the long‐term dependency information of the data and has good performance in solving the time series prediction problem [33]. However, LSTM also has certain drawbacks, such as computational complexity, and can only handle time series.…”
Section: Related Workmentioning
confidence: 99%
“…CNN is a neural network structure that has been developed in recent years and has attracted widespread attention. This network structure can effectively reduce the complexity of the network and can solve problems such as image processing [33], face recognition [34] and the obtained results are more accurate. CNN can reduce the number of parameters while ensuring accuracy.…”
Section: Related Workmentioning
confidence: 99%
“…In 1963, the American meteorologist E. N. Lorenz observed chaos in his atmospheric studies, opening the way for future exploration of chaos [ 1 ]. Chaos has favorable randomness and it is widely used in various fields such as secure communication [ 2 ], medical image processing [ 3 , 4 , 5 ], biomedical science [ 6 , 7 ], and finance [ 8 , 9 , 10 ]. In 1979, Otto Rössler proposed the first hyperchaotic system with two or more attractors and positive Lyapunov exponents, its phase orbitals can be separated in multiple directions, and the algebraic structure and dynamical behavior are more complex, confidential, and impenetrable than ordinary low-dimensional chaotic systems, with greater potential for research and development.…”
Section: Introductionmentioning
confidence: 99%
“…al. [8] has briefly discussed utilisation of medical research and technology in recent years. The chaotic recursive diagonal model's hybrid CNN method used for technical research, and its potential utility in medical image processing was investigated.…”
Section: Introductionmentioning
confidence: 99%