2,609 research outputs found
In the mood for travel: mobility, gender and nostalgia in Wong Kar-wai’s cinematic Hong Kong
The director Wong Kar-wai has been widely recognized as a key figure in contemporary Hong Kong cinema. His films have been seen through a number of critical lenses: as auteurist artworks (Brunette, 2005); as creative popular cinema (Bordwell, 2000); as highly political texts responding directly to the 1997 handover (Stokes and Hoover, 1999). Rather than focusing on an aesthetic, technical or political (in a narrow sense) interpretation, this thesis, using the approach of textual and contextual analysis, seeks to bring Wong’s films into dialogue with contemporary cultural theories about the nature of space, mobility, gender and nostalgia. In this way I hope both to re-position the films within the cultural context to which and of which they speak, and to show the ways in which they also speak to contemporary cultural concerns which far exceed it. Thus my argument is that these are globally significant films because of the paradigmatic nature of the specific Hong Kong culture which they explore, a culture which embodies in heightened form characteristics seen as typifying modern urban experience. In light of Bhabha’s theories of post-colonial culture (1994), Abbas’ suggestion of Hong Kong culture as indefinable “postculture” (1997), and Rey Chow’s analysis of Hong Kong’s post-colonial self-writing (1998), this thesis seeks to show how a marginal culture not only survives, but also creates a speaking position for today’s global culture through Wong’s cinema. The thesis is structured around three major themes, those of mobility, gender construction and nostalgia, all of which are both regionally specific concerns and global issues. Today, we see the dual trends of nationalism and globalization; the former brings exclusivity and the latter brings homogeneity. Wong’s films displays the creativity of Hong Kong’s post-colonial culture, whose hybridity and ambivalence defy these conservative trends and shed light on the future of global culture
Understanding the Role of Pathways in a Deep Neural Network
Deep neural networks have demonstrated superior performance in artificial
intelligence applications, but the opaqueness of their inner working mechanism
is one major drawback in their application. The prevailing unit-based
interpretation is a statistical observation of stimulus-response data, which
fails to show a detailed internal process of inherent mechanisms of neural
networks. In this work, we analyze a convolutional neural network (CNN) trained
in the classification task and present an algorithm to extract the diffusion
pathways of individual pixels to identify the locations of pixels in an input
image associated with object classes. The pathways allow us to test the causal
components which are important for classification and the pathway-based
representations are clearly distinguishable between categories. We find that
the few largest pathways of an individual pixel from an image tend to cross the
feature maps in each layer that is important for classification. And the large
pathways of images of the same category are more consistent in their trends
than those of different categories. We also apply the pathways to understanding
adversarial attacks, object completion, and movement perception. Further, the
total number of pathways on feature maps in all layers can clearly discriminate
the original, deformed, and target samples
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