[PDF] Top 20 Comparison of SVM and ANN for classification of eye events in EEG
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Comparison of SVM and ANN for classification of eye events in EEG
... The electroencephalogram, or EEG, consists of the elec- trical activity of relatively large neuronal populations that can be recorded from the scalp. In healthy adults, the amplitudes and frequencies of such ... See full document
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Wavelet Transform for Classification of EEG Signal using SVM and ANN
... order to overcome the problems related to Fourier transform, Fat Fourier Transform and Short Time Fourier transform, a powerful method was proposed in the late 1980s, known as Wavelet transform. Wavelet Transform can be ... See full document
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Comparison of ANN and SVM to Identify Children Handwriting Difficulties
... the classification results obtained for each attributes using ANN classifier and SVM ...The classification performance was divided into 2 parts: con- trol and ...the classification rate ... See full document
5
SVM and ANN Based Classification of Plant Diseases Using Feature Reduction Technique
... for classification of leaf ...The classification of disease type is performed using k-NN and an adaptive Bayes classifier using Gaussian mixture ...The classification results observed indicates that ... See full document
9
Epileptic Seizure Classification of EEG Image Using ANN
... SVM is another sort of classifier that is inspired by two ideas. To start with, changing information into a high dimensional space can change complex issues (with complex choice surfaces) into less difficult ... See full document
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Comparisons between motor area EEG and all-channels EEG for two algorithms in motor imagery task classification
... area EEG and all-channels EEG in the Brain Computer Interface (BCI) ...tasks classification. The CC-LS-SVM algorithm combines the cross-correlation (CC) technique and the least square support ... See full document
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Classification of Partial Discharge Measured under Different Levels of Noise Contamination
... work, comparison between different combinations of fea- ture extraction and classifiers was made to determine which method has the highest classifica- tion accuracy result or highest noise ... See full document
20
The Hybrid Technique for Image Classification to Detect Gender and Age using ANN and SVM
... gender classification and DCT Mod2 feature extraction, edge detection around eyes, mouth, nose and cheeks for age classification are ...pixel comparison file. In the classification mode, video ... See full document
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Internetworking Indonesia Journal
... in EEG signal analysis because these methods provide great performance in classification of EEG ...decomposed EEG signal from wavelet transform is used prior to the ANN ...the ... See full document
6
EEG Signal Classification Using ANN Trained With Hybrid PSO And GSA
... of EEG signals are used in the feature selection stage and further seizure detection is done using an ANN ...with SVM as a classifier in ...the classification of EEG signals into ... See full document
7
Emotion Classification from EEG Signals Using Time Frequency DWT Features and ANN
... in EEG signal as a result of involuntary muscle move- ment as such the blinking of eyes, or interference caused from the heartbeat car- diac electrical system, introducing unwanted spikes and distortion in the ... See full document
5
Predicting Diabetes Mellitus using Data Mining Techniques
... Diabetes is a dangerous disease with the potential to cause a worldwide Health Care crisis. According to International Diabetes confederation 382 million people are living with diabetes world wide. By 2035, this will be ... See full document
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Application of Image Processing for Classification and Quality Evaluation of Wheat
... world. Classification of different wheat varieties and determination of quality parameters of wheat are an important challenge for the food grain industry all over the ...of classification and qualification ... See full document
6
ANN vs. SVM : which one performs better in classification of MCCs in mammogram imaging
... the ANN classifier, the number of nodes in the hidden layer is empirically set as 15 for the better results ...our SVM implementation as it can generate particular good ...the SVM classifier include ... See full document
21
Hybrid Feature Based War Scene Classification using ANN and SVM: A Comparative Study
... The first neurological network model was introduced by McCulloch and Pitts [19]. The Hebbian rule[20] represents neural learning procedures, which implies that the connection between two neurons is strengthened when both ... See full document
9
EEG Based Classification of Hand Movements using BCI
... the EEG headset to collect the EEG signals from around 29 healthy participants or subjects between the age of 20 to 30 years with the duration of 30 ...8-channel EEG module ENOBIO 8 was used for ... See full document
5
Contralateral eye-to-eye comparison of intravitreal ranibizumab and a sustained-release dexamethasone intravitreal implant in recalcitrant diabetic macular edema
... of comparison of the DEX implant to shorter-acting steroids, other anti-VEGF agents, or to a switch to other such agents, and no combination therapy arm that examined treatment with both the DEX implant and ... See full document
6
A Review on Indian Sign Language Recognition
... Figure two shows the signs in ISL admire country alphabets A, B, C, D and E. ISL recognition is relatively new within the field of signing recognition. A sensible framework for ISL gesture primarily based human mechanism ... See full document
13
B cell and T cell Leukemia Classification using Genetic Algorithm, PCA, SVM and ANN
... Faroun et al.[11] Enhanced multi-classification process by choosing optimal features set, and then using this feature set as an input for training. Dimensionality of the data was reduced by selecting a subset. ... See full document
6
Image Object Classification and Identification using Soft Computing Tools: A Review
... KNN is a simple classification method with good accuracy. It depends on the majority vote of the k-nearest neighbour classes. Thus the result can be considered as the best fit class for that point. For example if ... See full document
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