Applications of Convolutional Neural Networks (CNNs) to various problems have been the subject of a number of recent studies ranging from image classification and object detection to scene parsing, segmentation 3D volumetric images and action recognition in videos. CNNs are able to learn input data representation, instead of using fixed engineered features. In this study, the image model traine...

The purpose of this study is to examine and analyze the influence availability movie genre, service quality, quality Netflix user satisfaction in Indonesia. This type research quantitative research. variables are satisfaction. data collection technique used a questionnaire with Likert scale measurement scale. number samples 85 samples. analysis multiple linear regression SPSS program. findings ...

In recent years linguistic research has turned increasing attention to covert/overt strategies to modulate authorial stance and positioning in scientific texts, and to the recipients' response. This study discussed some theoretical implications of the use of rhetoric in scientific communication and analysed qualitative data from the authoritative The Cognitive Neurosciences III (2004) volume. I...

In order to predict user-favorite songs, managing user preferences information and genre classification are necessary. In this paper, we propose a preference classification about content based on real-time user brainwave and a music recommendation system based on it. We focused on classifying real-time user preferences by analyzing the user’s brainwaves. The brainwaves are acquired using a wire...

Recently many research has been conducted to retrieve pertinent parameters and adequate models for automatic music genre classification. In this paper, two measures based upon information theory concepts are investigated for mapping the features space to decision space. A Gaussian Mixture Model (GMM) is used as a baseline and reference system. Various strategies are proposed for training and te...

This article demonstrates the importance of considering transgender speakers apart from gays, lesbians, and bisexuals, even where there is significant overlap in the linguistic practices of these groups. Through an analysis of transgender coming out narratives, it is shown that previous accounts of this genre, which have focused on gays and lesbians, do not extend to the entire LGBT (lesbian, g...

A hierarchical framework is proposed to address the issues of modeling different type of words in keyword spotting (KWS). Keyword models are built at various levels according to the availability of training set resources for each individual word. The proposed approach improves the performance of KWS even when no training speech is available for the keywords. It also suggests an easier way to co...