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Many computer vision applications, such as scene analysis and medical image interpretation, are ill-suited for traditional classification where each image can only be associated with a single class. This has stimulated recent work in multi-label learning where a given image can be tagged with multiple class labels. A serious problem with existing approaches(More)
The goal of automatic image annotation is to automatically generate annotations for images to describe their content. In the past, statistical machine translation models have been successfully applied to automatic image annotation task [8]. It views the process of annotating images as a process of translating the content from a 'visual language' to textual(More)
Spectral clustering enjoys its success in both data clustering and semisupervised learning. But, most spectral clustering algorithms cannot handle multi-class clustering problems directly. Additional strategies are needed to extend spectral clustering algorithms to multi-class clustering problems. Furthermore, most spectral clustering algorithms employ hard(More)
Statistical learning techniques provide a robust framework for learning representations of semantic concepts from multimedia features. The bottleneck is the number of training samples needed to construct robust models. This is particularly expensive when the annotation needs to happen at finer granularity. We present a novel approach where the annotations(More)
Video annotation is an expensive but necessary task for most vision and learning problems that require building models of visual semantics. This annotation gets prohibitively expensive especially when annotation has to happen at finer grained levels of regions in the videos. One way around the finer grained annotation dilemma is to support annotation at(More)
One of the keys issues to content-based image retrieval is the similarity measurement of images. Images are represented as points in the space of low-level visual features and most similarity measures are based on certain distance measurement between these features. Given a distance metric, two images with shorter distance are deemed to more similar than(More)
This article has proposed a new method for designing and studying engine intake system based on the technology of CAD/CAE/CFD integration. Firstly, according to the similarity principle and pressure wave theory, the structure parameters of target engine intake system were defined referencing the similar engine. Then, the intake system parameters were input(More)
Based on simulation software GT-drive, the author analyzed the transmission system performance of a passenger car with diesel engine and provided the appropriate research methods. Firstly, the numerical simulation model of a vehicle was built based on vehicle weight, frontal area, rolling, air-drag coefficient, etc. The different matching schemes were(More)
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