A new unsupervised convolutional neural network model for Chinese scene text detection

As one of the most popular deep learning models, convolution neural network (CNN) has achieved huge success in image information extraction. Traditionally CNN is trained by supervised learning method with labeled data and used as a classifier by adding a classification layer in the end. Its capability of extracting image features is largely limited due to the difficulty of setting up a large training dataset. In this paper, we propose a new unsupervised learning CNN model, which uses a so-called convolutional sparse auto-encoder (CSAE) algorithm pre-Train the CNN. Instead of using labeled natural images for CNN training, the CSAE algorithm can be used to train the CNN with unlabeled artificial images, which enables easy expansion of training data and unsupervised learning. The CSAE algorithm is especially designed for extracting complex features from specific objects such as Chinese characters. After the features of articficial images are extracted by the CSAE algorithm, the learned parameters are used to initialize the first CNN convolutional layer, and then the CNN model is fine-Trained by scene image patches with a linear classifier. The new CNN model is applied to Chinese scene text detection and is evaluated with a multilingual image dataset, which labels Chinese, English and numerals texts separately. More than 10% detection precision gain is observed over two CNN models.

Active Foreground Region Extraction and Tracking for Sports Video Annotation

Automatic video segmentation plays a vital role in sports videos annotation. This paper presents a fully automatic and computationally efficient algorithm for analysis of sports videos. Various methods of automatic shot boundary detection have been proposed to perform automatic video segmentation. These investigations mainly concentrate on detecting fades and dissolves for fast processing of the entire video scene without providing any additional feedback on object relativity within the shots. The goal of the proposed method is to identify regions that perform certain activities in a scene. The model uses some low-level feature video processing algorithms to extract the shot boundaries from a video scene and to identify dominant colours within these boundaries. An object classification method is used for clustering the seed distributions of the dominant colours to homogeneous regions. Using a simple tracking method a classification of these regions to active or static is performed. The efficiency of the proposed framework is demonstrated over a standard video benchmark with numerous types of sport events and the experimental results show that our algorithm can be used with high accuracy for automatic annotation of active regions for sport videos.

Gesturing elsewhere: the identity politics of the Balinese death/thrash metal scene

This essay explores the political significance of Balinese death/thrash fandom. In the early 1990s, the emergence of a death/thrash scene in Bali paralleled growing criticism of accelerated tourism development on the island. Specifically, locals protested the increasing ubiquity of Jakarta, 'the centre', cast as threatening to an authentically 'low', peripheral Balinese culture. Similarly, death/thrash enthusiasts also gravitated toward certain fringes, although they rejected dominant notions of Balinese-ness by gesturing elsewhere, toward a global scene. The essay explores the ways in which death/thrash enthusiasts engaged with local discourses by coveting their marginality, and aims to demonstrate how their articulations of 'alien-ness' contributed in important ways to a broader regionalism.

Creating a scene: Balinese punk's beginnings

The promotion of alternative music by deregulated television and recording industries, together with the increasingly felt presence of the metropolis, converged on Balinese cultural and physical landscapes in the 1990s. Mirroring developments in broader society, a regionalist discourse, which polarized notions of ‘centre’ and ‘periphery’, emerged among Balinese youth in the context of the local band scene. For certain musicians, musical authenticity was firmly rooted in a cultural and geographical locale, and was articulated by their abhorrence for socializing at shopping malls. In contrast, these Balinese alternative (including punk) musicians sought authenticity in a metropolitan elsewhere. This article is a case study of the indigenization of a ‘global’ code in a non-western periphery. It contests arguments for the ‘post-imperial’ nature of globalization, and demonstrates the continued salience of centre–periphery dialectics in local discourses. At the same time, the study attests to the progressive role a metropolitan superculture can play in cultural renewal in the periphery.

Automating the extraction of quantities

The Automated Estimator and LCADesign are two early examples of nD modelling software which both rely on the extraction of quantities from CAD models to support their further processing. The issues of building information modelling (BIM), quantity takeoff for different purposes and automating quantity takeoff are discussed by comparing the aims and use of the two programs. The technical features of the two programs are also described. The technical issues around the use of 3D models is described together with implementation issues and comments about the implementation of the IFC specifications. Some user issues that emerged through the development process are described, with a summary of the generic research tasks which are necessary to fully support the use of BIM and nD modelling.

High Culture as Subculture : Brisbane's Contemporary Chamber Music Scene

The aim of the dissertation is to discover the extent to which methodologies and conceptual frameworks used to understand popular culture may also be useful in the attempt to understand contemporary high culture. The dissertation addresses this question through the application of subculture theory to Brisbane’s contemporary chamber music scene, drawing on a detailed case study of the contemporary chamber ensemble Topology and its audiences. The dissertation begins by establishing the logic and necessity of applying cultural studies methodologies to contemporary high culture. This argument is supported by a discussion of the conceptual relationships between cultural studies, high culture, and popular culture, and the methodological consequences of these relationships. In Chapter 2, a brief overview of interdisciplinary approaches to music reveals the central importance of subculture theory, and a detailed survey of the history of cultural studies research into music subcultures follows. Five investigative themes are identified as being crucial to all forms of contemporary subculture theory: the symbolic; the spatial; the social; the temporal; the ideological and political. Chapters 3 and 4 present the findings of the case study as they relate to these five investigative themes of contemporary subculture theory. Chapter 5 synthesises the findings of the previous two chapters, and argues that while participation in contemporary chamber music is not as intense or pervasive as is the case with the most researched street-based youth subcultures, it is nevertheless possible to describe Brisbane’s contemporary chamber music scene as a subculture. The dissertation closes by reflecting on the ways in which the subcultural analysis of contemporary chamber music has yielded some insight into the lived practices of high culture in contemporary urban contexts.

Toward a fuzzy domain ontology extraction method for adaptive e-learning

With the widespread applications of electronic learning (e-Learning) technologies to education at all levels, increasing number of online educational resources and messages are generated from the corresponding e-Learning environments. Nevertheless, it is quite difficult, if not totally impossible, for instructors to read through and analyze the online messages to predict the progress of their students on the fly. The main contribution of this paper is the illustration of a novel concept map generation mechanism which is underpinned by a fuzzy domain ontology extraction algorithm. The proposed mechanism can automatically construct concept maps based on the messages posted to online discussion forums. By browsing the concept maps, instructors can quickly identify the progress of their students and adjust the pedagogical sequence on the fly. Our initial experimental results reveal that the accuracy and the quality of the automatically generated concept maps are promising. Our research work opens the door to the development and application of intelligent software tools to enhance e-Learning.