Classification inter-frame prediction algorithm for H.264

Yang, Xiuzhi; Zheng, Mingbo; Xue, L.

doi:10.3724/sp.j.1187.2012.00939

Cited by 1 publication

(6 citation statements)

References 3 publications

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“…After multiple experiments, the optimal coefficient of the model was obtained. The accuracy achieved with this coefficient is 0.941 [5].…”

Section: Traditional Machine Learning Methods Of Mri Brain Image Clas...mentioning

confidence: 90%

“…In a previous Zhan Shu et al study, random forests were used for MRI brain image classification [5]. In terms of feature extraction for brain MRI images, this study takes texture, grayscale, histogram features, Otsu threshold, and shape features [5]. The diversified feature extraction in this study can enrich the expression of image features.…”

Section: Traditional Machine Learning Methods Of Mri Brain Image Clas...mentioning

confidence: 97%

“…In MRI medical imaging, due to various influences on the imaging process, such as tissue movement and artifacts caused by metal implants in the body, medical images inevitably have characteristics such as blurred edges of various tissues and uneven regional grayscale [5]. These will bring many difficulties to correctly classifying MRI brain imaging categories.…”

Section: Traditional Machine Learning Methods Of Mri Brain Image Clas...mentioning

confidence: 99%

“…Support Vector Machine (SVM) is a classic classifier performing well in sample, high-dimensional, and nonlinear sample learning [5]. SVM has also been proposed in imaging to classify MRI images.…”

Section: Traditional Machine Learning Methods Of Mri Brain Image Clas...mentioning

confidence: 99%

“…Random forest is a combination classifier in machine learning, which can also achieve high accuracy in classification. In a previous Zhan Shu et al study, random forests were used for MRI brain image classification [5]. In terms of feature extraction for brain MRI images, this study takes texture, grayscale, histogram features, Otsu threshold, and shape features [5].…”

Section: Traditional Machine Learning Methods Of Mri Brain Image Clas...mentioning

confidence: 99%

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Deep learning-based image classification of MRI brain image

Xie

2023

TNS

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This article reviews the latest research on MRI brain image classification techniques based on deep learning. Firstly, MRI brain image classification and traditional machine learning methods applied to MRI image classification were briefly introduced. Then, a review was conducted on existing MRI brain image classification methods based on deep learning. The article reviews past and recent related research and provides a detailed introduction to the application of deep learning methods in MRI brain image classification. This includes some traditional machine learning methods and research achievements in deep neural networks (DNN), convolutional neural networks (CNN), and transfer learning. The most commonly used deep learning architecture for image classification is CNN. Research has shown that deep learning methods have high accuracy and performance in MRI brain image classification and can automatically extract image features for effective classification. Therefore, deep learning methods provide doctors with more comprehensive information, help them make more accurate diagnoses and formulate treatment plans, and have broad prospects for application in MRI brain image classification. In the future, the further development of deep learning technology will achieve better auxiliary effects on diagnosis, treatment, and scientific research related to the brain.

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“…After multiple experiments, the optimal coefficient of the model was obtained. The accuracy achieved with this coefficient is 0.941 [5].…”

Section: Traditional Machine Learning Methods Of Mri Brain Image Clas...mentioning

confidence: 90%

Section: Traditional Machine Learning Methods Of Mri Brain Image Clas...mentioning

confidence: 97%

Section: Traditional Machine Learning Methods Of Mri Brain Image Clas...mentioning

confidence: 99%

Section: Traditional Machine Learning Methods Of Mri Brain Image Clas...mentioning

confidence: 99%

Section: Traditional Machine Learning Methods Of Mri Brain Image Clas...mentioning

confidence: 99%

See 3 more Smart Citations

Deep learning-based image classification of MRI brain image

Xie

2023

TNS

View full text Add to dashboard Cite

show abstract

Classification inter-frame prediction algorithm for H.264

Cited by 1 publication

References 3 publications

Deep learning-based image classification of MRI brain image

Deep learning-based image classification of MRI brain image

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