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In this paper, an algorithm, named CCHN, is proposed to solve the partitional clustering problem. An outer chaotic mechanism with annealing strategy is introduced into the competitive Hopfield neural network to construct CCHN for expecting better opportunities of converging to the optimal solution. In addition to retain the competitive characteristics of the conventional competitive Hopfield neural...
With the increasing use of audio sensors in user generated content collection, how to detect semantic concepts using audio streams has become an important research problem. In this paper, we present a semantic concept annotation system using soundtracks/ audio of the video. We investigate three different acoustic feature representations for audio semantic concept annotation and explore fusion of audio...
In this paper, a novel hybrid evolutionary algorithm combining a Hopfield net and a local search strategy is proposed to solve maximum clique problem. The algorithm makes full use of powerful searching capability of Hopfield net and probabilistic statistic feature of estimation of distribution algorithm to produce wider search in global solution domain. In particular, a possible extension way correlated...
Emotion recognition from speech is a challenging research area with wide applications. In this paper we explore one of the key aspects of building an emotion recognition system: generating suitable feature representation. We extract features from four angles: (1) low-level acoustic features such as intensity, F0, jitter, shimmer and spectral contours etc. and statistical functions over these features,...
Given the proliferation of geo-tagged images, geo-aware image classification is an emerging topic. To derive a better image representation, tag features which represents an image as a histogram of tags are recently introduced. However, it is unclear whether geo tags can improve the tag features. To resolve the uncertainty, this paper studies geo-aware tag features. Our work is based on previous work...
Learning video concept detectors from social media sources, such as Flickr images and YouTube videos, has the potential to address a wide variety of concept queries for video search. While the potential has been recognized by many, and progress on the topic has been impressive, we argue that two key questions, i.e., What visual tagging source is most suited for selecting positive training examples...
Transmission characteristics of photon in the subgrade tissue is the theoretical basis of using laser imaging to detect density of compacted subgrade. After explaining the basic methods of using Monte Carlo simulation theory to study the propagation of photon in the subgrade tissue, the paper selects optical properties of several subgrade tissues, simulates the propagation of photon in the subgrade...
Automatic image tagging is important yet challenging due to the semantic gap and the lack of learning examples to model a tag's visual diversity. Meanwhile, social user tagging is creating rich multimedia content on the Web. In this paper, we propose to combine the two tagging approaches in a search-based framework. For an unlabeled image, we first retrieve its visual neighbors from a large user-tagged...
Quite recently, a few hundreds of semantic concepts are detected automatically with varied performance and subsequently, a new video retrieval paradigm of query-by-concept emerges. In this paper, we consider the problem of exploiting the potential of learned semantics concepts, together with the combination of traditional methods, for automatic and interactive retrieval. We argue that it is important,...
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