1 Background: Instagram (a popular image-based social media app) with millions of posts each day can be used to inform public health interventions and policies but current research relying on image-based data often relies on hand coding of images which is time consuming, costly, and may be subject to researcher bias. What is more, current best practices in automated image classification (e.g., ...

Abstract: Classification of the cervical cell is one of the most important and crucial tasks in the medical image analysis. Due to its importance, the aim of the paper is to investigate about the classification of Cervical Cell as Normal Cell or Abnormal Cell by using individual feature extraction method and combining individual feature extraction features method with the classification techniq...

This paper proposes a method to detect the errors in synthetic speech of a unit selection speech synthesis system automatically using log likelihood ratio and support vector machine (SVM). For SVM training, a set of synthetic speech are firstly generated by a given speech synthesis system and their synthetic errors are labeled by manually annotating the segments that sound unnatural. Then, two ...

The use of SVM (Support Vector Machines) in detecting e-mail as spam or nonspam by incorporating feature selection using GA (Genetic Algorithm) is investigated. An GA approach is adopted to select features that are most favorable to SVM classifier, which is named as GA-SVM. Scaling factor is exploited to measure the relevant coefficients of feature to the classification task and is estimated by...

Aiming at the problems of the slow convergence speed of general partial binary tree support vector machine (SVM) classifier and the fault samples easy to accumulate caused by complete binary tree and partial binary tree SVM classifier. The thesis proposes a multi-category classification method based on the unbalanced binary tree support vector machine (SVM),which construct a unbalanced binary t...

Cervical cancer is the second most common gynaecologic cancer worldwide. Unlike the other cancers it does not show any symptoms in its earlier stage which causes mortality among women. It takes 8 to 10 years to develop from precancerous to severe stage. The important reasons for higher cervical cancer in developing countries are lack of resources, lack of effectual screening programs and inadeq...

This paper presents a gene selection method for classification of gene expression data. First, a fFeature selection techniques based on t-test statistic is used applied in order to select the n topranked significant genes. Then, a combination of Genetic Algorithm (GA) and /Support Vector Machines (SVM) is used to further select significant genes to the resulting set of genes obtained from t-tes...

Lung cancer is one of the deadly and most common diseases in the world. Radiologists fail to diagnose small pulmonary nodules in as many as 30% of positive cases. Many methods have been proposed in the literature such as neural network algorithms. Recently, support vector machines (SVM)'s had received an increasing attention for pattern recognition. The advantage of SVM lies in better modeling ...

In this work we describe an application of the Support Vector Machine (SVM) classifier for the segmentation of wounds in color images. The SVM-based segmentation combines naturally a high dimensional space of image features into a single classification machine. Since particular choice of image features is crucial for the performance of SVM classifier, we investigate the efficiency of colorand t...

Effectiveness of Artificial Neural Networks (ANN) and Support Vector Machines (SVM) classifiers for fault diagnosis of rolling element bearings are presented in this paper. The characteristic features of vibration signals of rotating driveline that was run in its normal condition and with faults introduced were used as input to ANN and SVM classifiers. Simple statistical features such as standa...