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Automatically describing video content with natural language is a fundamental challenge of computer vision. Recurrent Neural Networks (RNNs), which models sequence dynamics, has attracted increasing attention on visual interpretation. However, most existing approaches generate a word locally with the given previous words and the visual content, while the(More)
The problem of tagging is mostly considered from the perspectives of machine learning and data-driven philosophy. A fundamental issue that underlies the success of these approaches is the visual similarity, ranging from the nearest neighbor search to manifold learning, to identify similar instances of an example for tag completion. The need to searching for(More)
While there has been increasing interest in the task of describing video with natural language, current computer vision algorithms are still severely limited in terms of the variability and complexity of the videos and their associated language that they can recognize. This is in part due to the simplicity of current benchmarks, which mostly focus on(More)
One of the fundamental problems in image search is to learn the ranking functions, i.e., similarity between the query and image. The research on this topic has evolved through two paradigms: feature-based vector model and image ranker learning. The former relies on the image surrounding texts, while the latter learns a ranker based on human labeled(More)
One of the fundamental problems in image search is to rank image documents according to a given textual query. We address two limitations of the existing image search engines in this paper. First, there is no straightforward way of comparing textual keywords with visual image content. Image search engines therefore highly depend on the surrounding texts,(More)
The etiological role of dysregulated autophagy in neurodegenerative diseases has been a subject of intense investigation. While manganese (Mn) is known to cause dopaminergic (DAergic) neurodegeneration, it has yet to be determined whether the dysregulation of autophagy plays a role in Mn-induced neuronal injury. In this study, we investigated the effect of(More)
Lead (Pb) is a well-known heavy metal in nature. Pb can cause pathophysiological changes in several organ systems including central nervous system. Especially, Pb can affect intelligence development and the ability of learning and memory of children. However, the toxic effects and mechanisms of Pb on learning and memory are still unclear. To clarify the(More)
Manganese has been known to induce neurological disorders. In the present study, we determined the effect of manganese on the expression of α-synuclein in PC12 cells and its role in manganese-induced cytotoxicity. We also investigated the relationship between α-synuclein expression and the change of ERK1/2 MAPK activity. In our research, manganese exposure(More)
Manganese has been known to induce neurological disorders similar to Parkinson's disease. The dysfunction of ubiquitin-proteasome system, a pathway involved in detoxification and targeting of damaged proteins, is connected with Parkinson's disease pathogenesis. Oxidative stress may be involved in Parkinson's disease, and may also be associated with(More)