The effectiveness of mutation testing depends heavily on the types of faults that the mutation operators are designed to represent. Therefore, the quality of the mutation operators is key to mutation testing. Mutation testing has traditionally been applied to procedural-based languages, and mutation operators have been developed to support most of their language features. Object-oriented progra...

This paper examines the use of interdependencies of parameter classes in transformation-based speaker adaptation algorithms such as maximum likelihood linear regression (MLLR). In transformation-based adaptation, increasing the number of transformation classes can provide more detailed information for adaptation, but at the expense of greater estimation error with small amounts of data. In this...

human action recognition is an important problem in computer vision. one of the methods that are recently used is sparse coding. conventional sparse coding algorithms learn dictionaries and codes in an unsupervised manner and neglect class information that is available in the training set. but in this paper for solving this problem, we use a discriminative sparse code based on multi-manifolds. ...

Text classification is an active research area motivated by many real-world applications. Even so, research formulations and prototypes often make assumptions that are not suitable for deployment. For example, in many real applications, the set of class labels keeps evolving, continual user feedback must be integrated into the classifier, and test documents may come from a population statistica...

Automatic classification of aquatic microorganisms is based on the morphological features extracted from individual images. The current works their do not consider inter-class similarity and intra-class variance that causes misclassification. We are particularly interested in case where within a class occurs due to discrete visual changes microscopic In this paper, we propose account for it by ...

purposes: the aim of this study was to evaluate the intra and inter-examiner reliability and reproducibility of linear measurements in cone-beam tomography (cbct) images taken by calibrated radiologists and periodontists. materials and methods: the alveolar ridge dimensions in selected cbct images were measured by two calibrated radiologists and two periodontists. intra and inter-examiner relia...

Machine learning algorithms are often faced with several data related problems. Real-world datasets come in various types and dimensions, each of which constitute some form problems; moreover, they contain irrelevant or noisy features. As a result these, different problems require techniques for the classification process. In this paper, interest replicated synthetic order to investigate evalua...

This paper presents an evaluation of how data augmentation and inter-class transformations can be used to synthesize training in low-data scenarios for single-image weather classification. In such scenarios, augmentations is a critical component, but there limit much improvements gained using classical strategies. Generative adversarial networks (GAN) have been demonstrated generate impressive ...