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Binary PSO with mutation operator for feature selection using decision tree applied to spam detection
In this paper, we proposed a novel spam detection method that focused on reducing the false positive error of mislabeling nonspam as spam. First, we used the wrapper-based feature selection method toExpand
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  • Open Access
Detection of subjects and brain regions related to Alzheimer's disease using 3D MRI scans based on eigenbrain and machine learning
Purpose: Early diagnosis or detection of Alzheimer's disease (AD) from the normal elder control (NC) is very important. However, the computer-aided diagnosis (CAD) was not widely used, and theExpand
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  • Open Access
Facial Emotion Recognition Based on Biorthogonal Wavelet Entropy, Fuzzy Support Vector Machine, and Stratified Cross Validation
Emotion recognition represents the position and motion of facial muscles. It contributes significantly in many fields. Current approaches have not obtained good results. This paper aimed to propose aExpand
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Fruit classification using computer vision and feedforward neural network
Abstract Fruit classification is a difficult challenge due to the numerous types of fruits. In order to recognize fruits more accurately, we proposed a hybrid classification method based onExpand
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Classification of Alzheimer’s Disease Based on Eight-Layer Convolutional Neural Network with Leaky Rectified Linear Unit and Max Pooling
Alzheimer’s disease (AD) is a progressive brain disease. The goal of this study is to provide a new computer-vision based technique to detect it in an efficient way. The brain-imaging data of 98 ADExpand
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Identification of Green, Oolong and Black Teas in China via Wavelet Packet Entropy and Fuzzy Support Vector Machine
To develop an automatic tea-category identification system with a high recall rate, we proposed a computer-vision and machine-learning based system, which did not require expensive signal acquiringExpand
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  • Open Access
Pathological brain detection in MRI scanning by wavelet packet Tsallis entropy and fuzzy support vector machine
An computer-aided diagnosis system of pathological brain detection (PBD) is important for help physicians interpret and analyze medical images. We proposed a novel automatic PBD to distinguishExpand
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Magnetic resonance brain image classification based on weighted‐type fractional Fourier transform and nonparallel support vector machine
To classify brain images into pathological or healthy is a key pre‐clinical state for patients. Manual classification is tiresome, expensive, time‐consuming, and irreproducible. In this study, weExpand
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Feed‐forward neural network optimized by hybridization of PSO and ABC for abnormal brain detection
Automated and accurate classification of MR brain images is of crucially importance for medical analysis and interpretation. We proposed a novel automatic classification system based on particleExpand
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Detection of Pathological Brain in MRI Scanning Based on Wavelet-Entropy and Naive Bayes Classifier
An accurate diagnosis is important for the medical treatment of patients suffered from brain disease. Nuclear magnetic resonance images are commonly used by technicians to assist the pre-clinicalExpand
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