针对复杂环境下含标签货物实时记录困难的问题,提出一种面向视觉物联网(visual Internet of Things,VIoT)的文本检测方法。在视觉物联网中设计并引入基于全局上下文注意力和坐标注意力的文本检测网络(text detection network based on g...针对复杂环境下含标签货物实时记录困难的问题,提出一种面向视觉物联网(visual Internet of Things,VIoT)的文本检测方法。在视觉物联网中设计并引入基于全局上下文注意力和坐标注意力的文本检测网络(text detection network based on global context attention and coordinate attention,GCANet),首先提出一种改进型坐标注意力模块,通过水平和垂直2个并行的一维池化操作,避免了因二维全局池化造成的位置信息丢失;然后引入全局上下文注意力模块,避免在复杂的背景对文本检测的影响,并防止密集或较远间隔的文本被错误地检测。该系统中提出的GCANet在公共数据集ICDAR2015、MSRA-TD500和Total-Text上的综合指标F值分别达到87.4%、86.9%和86.3%。在工业标签数据集Label-Text上平均准确率、平均召回率和平均F值分别达到93.4%、90.9%和92.1%。此外,GCANet在矿井下的标签数据集Mine-Text上准确率、召回率和F值分别达到94.4%、84.9%和89.9%。实验结果表明,本文提出的面向视觉物联网的文本检测方法效果优异。展开更多
The global context(GC) descriptor is improved for describing interest regions,uses gradient orientation for binning,and thus provides more robust invariance for geometric and photometric transformations.The performanc...The global context(GC) descriptor is improved for describing interest regions,uses gradient orientation for binning,and thus provides more robust invariance for geometric and photometric transformations.The performance of the improved GC(IGC) to image matching is studied through extensive experiments on the Oxford A?ne dataset.Empirical results indicate that the proposed IGC yields quite stable and robust results,signi?cantly outperforms the original GC,and also can outperform the classical scale-invariant feature transform(SIFT) in most of the test cases.By integrating the IGC to the SIFT,the resulting of hybrid SIFT+IGC performs best over all other single descriptors in these experimental evaluations with various geometric transformations.展开更多
Cognition and pain share common neural substrates and interact reciprocally: chronic pain compromises cognitive performance, whereas cognitive processes modulate pain perception. In the present study, we established a...Cognition and pain share common neural substrates and interact reciprocally: chronic pain compromises cognitive performance, whereas cognitive processes modulate pain perception. In the present study, we established a non-drug-dependent rat model of context-based analgesia,where two different contexts(dark and bright) were matched with a high(52°C) or low(48°C) temperature in the hot-plate test during training. Before and after training,we set the temperature to the high level in both contexts.Rats showed longer paw licking latencies in trials with the context originally matched to a low temperature than those to a high temperature, indicating successful establishment of a context-based analgesic effect in rats. This effect was blocked by intraperitoneal injection of naloxone(an opioid receptor antagonist) before the probe. The context-based analgesic effect also disappeared after optogenetic activation or inhibition of the bilateral infralimbic or prelimbic sub-region of the prefrontal cortex. In brief, we established a context-based, non-drug dependent, placebo-like analgesia model in the rat. This model provides a new and useful tool for investigating the cognitive modulation of pain.展开更多
文摘针对复杂环境下含标签货物实时记录困难的问题,提出一种面向视觉物联网(visual Internet of Things,VIoT)的文本检测方法。在视觉物联网中设计并引入基于全局上下文注意力和坐标注意力的文本检测网络(text detection network based on global context attention and coordinate attention,GCANet),首先提出一种改进型坐标注意力模块,通过水平和垂直2个并行的一维池化操作,避免了因二维全局池化造成的位置信息丢失;然后引入全局上下文注意力模块,避免在复杂的背景对文本检测的影响,并防止密集或较远间隔的文本被错误地检测。该系统中提出的GCANet在公共数据集ICDAR2015、MSRA-TD500和Total-Text上的综合指标F值分别达到87.4%、86.9%和86.3%。在工业标签数据集Label-Text上平均准确率、平均召回率和平均F值分别达到93.4%、90.9%和92.1%。此外,GCANet在矿井下的标签数据集Mine-Text上准确率、召回率和F值分别达到94.4%、84.9%和89.9%。实验结果表明,本文提出的面向视觉物联网的文本检测方法效果优异。
基金the National Natural Science Foundation of China(Nos.60970109 and 61170228)
文摘The global context(GC) descriptor is improved for describing interest regions,uses gradient orientation for binning,and thus provides more robust invariance for geometric and photometric transformations.The performance of the improved GC(IGC) to image matching is studied through extensive experiments on the Oxford A?ne dataset.Empirical results indicate that the proposed IGC yields quite stable and robust results,signi?cantly outperforms the original GC,and also can outperform the classical scale-invariant feature transform(SIFT) in most of the test cases.By integrating the IGC to the SIFT,the resulting of hybrid SIFT+IGC performs best over all other single descriptors in these experimental evaluations with various geometric transformations.
基金supported by grants from the National Natural Science Foundation of China (91732107, 31200835, 81571067, and 81521063)the National Basic Research Development Program (973 Program) of China (2014CB548200 and 2015CB554503)
文摘Cognition and pain share common neural substrates and interact reciprocally: chronic pain compromises cognitive performance, whereas cognitive processes modulate pain perception. In the present study, we established a non-drug-dependent rat model of context-based analgesia,where two different contexts(dark and bright) were matched with a high(52°C) or low(48°C) temperature in the hot-plate test during training. Before and after training,we set the temperature to the high level in both contexts.Rats showed longer paw licking latencies in trials with the context originally matched to a low temperature than those to a high temperature, indicating successful establishment of a context-based analgesic effect in rats. This effect was blocked by intraperitoneal injection of naloxone(an opioid receptor antagonist) before the probe. The context-based analgesic effect also disappeared after optogenetic activation or inhibition of the bilateral infralimbic or prelimbic sub-region of the prefrontal cortex. In brief, we established a context-based, non-drug dependent, placebo-like analgesia model in the rat. This model provides a new and useful tool for investigating the cognitive modulation of pain.
