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1.
To save bandwidth and storage space as well as speed up data transmission, people usually perform lossy compression on images. Although the JPEG standard is a simple and effective compression method, it usually introduces various visually unpleasing artifacts, especially the notorious blocking artifacts. In recent years, deep convolutional neural networks (CNNs) have seen remarkable development in compression artifacts reduction. Despite the excellent performance, most deep CNNs suffer from heavy computation due to very deep and wide architectures. In this paper, we propose an enhanced wide-activated residual network (EWARN) for efficient and accurate image deblocking. Specifically, we propose an enhanced wide-activated residual block (EWARB) as basic construction module. Our EWARB gives rise to larger activation width, better use of interdependencies among channels, and more informative and discriminative non-linearity activation features without more parameters than residual block (RB) and wide-activated residual block (WARB). Furthermore, we introduce an overlapping patches extraction and combination (OPEC) strategy into our network in a full convolution way, leading to large receptive field, enforced compatibility among adjacent blocks, and efficient deblocking. Extensive experiments demonstrate that our EWARN outperforms several state-of-the-art methods quantitatively and qualitatively with relatively small model size and less running time, achieving a good trade-off between performance and complexity. 相似文献
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This study investigates the impact of lighting colors on subjective judgments of fabric: in particular, whether the influence of lighting varies depending on fabric types and color combinations. We conducted two visual assessments. In Study 1 (N = 44), eight illuminants and six types of fabric were presented as cloth stimuli. Derived from the literature review, four sets of adjectives (humble-luxurious, cool-warm, old-new, and not preferred-preferred) were used as metrics. In Study 2 (N = 41), five sets of fabric color combination swatches were assessed under lighting conditions that were identical to those of Study 1. Three bipolar scales (ordinary-characterful, classic-modern, and soft-rigid), were employed from factor analysis along with three unipolar scales (luxurious, preferred, harmonious with lighting). The results showed that hue characteristics of lighting and cloth types influenced participants' perceptions of the fabric. Overall, white lighting with 4000 K was the most preferred and luxurious lighting across various types of clothes, while a pinkish white with 4700 K (duv = −0.0127) was the best matched in every color combination. In addition, there were interaction effects between lighting colors, clothes types, and fabric color combinations with regard to each of the perceptual qualities. This study provides empirical evidence for optimally match lighting colors with fabric in the presentation of fabric goods. 相似文献
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AbstractModel order reduction is a common practice to reduce large order systems so that their simulation and control become easy. Nonlinearity aware trajectory piecewise linear is a variation of trajectory piecewise linearization technique of order reduction that is used to reduce nonlinear systems. With this scheme, the reduced approximation of the system is generated by weighted sum of the linearized and reduced sub-models obtained at certain linearization points on the system trajectory. This scheme uses dynamically inspired weight assignment that makes the approximation nonlinearity aware. Just as weight assignment, the process of linearization points selection is also important for generating faithful approximations. This article uses a global maximum error controller based linearization points selection scheme according to which a state is chosen as a linearization point if the error between a current reduced model and the full order nonlinear system reaches a maximum value. A combination that not only selects linearization points based on an error controller but also assigns dynamic inspired weights is shown in this article. The proposed scheme generates approximations with higher accuracies. This is demonstrated by applying the proposed method to some benchmark nonlinear circuits including RC ladder network and inverter chain circuit and comparing the results with the conventional schemes. 相似文献
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针对电力市场用户群庞大,交易过程中售电套餐选择困难的问题,在Spark环境下设计了一种售电套餐推荐方法,同时也解决了售电套餐推荐过程中在大数据环境下的可扩展性及实时性问题。首先,计算出每个套餐属性的权重值,从而计算得到售电套餐综合相似度。然后,计及用户和套餐两方面提出一种售电套餐推荐方法,实现售电套餐的精准推荐。实验表明,提出的推荐方法能够明显提高推荐的准确度,并且在分布式环境下具有良好的推荐效率和可扩展性。 相似文献
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为了提高注入剖面测井的准确性,研制了一种新型注入剖面组合测井仪。该仪器由流量处理单元、伽马处理单元、井温处理单元、磁性定位处理单元、调制式传输、电源电路六部分组成。一次下井可同时测取流量、伽马、井温、磁性定位四组参数。具有测取资料精度高、单芯电缆传输、流量可单点测量也可连续测量以厦现场监测和维修方便等特点。 相似文献
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廊固凹陷大兴断层对油气分布的控制研究 总被引:6,自引:0,他引:6
廊固凹陷断裂系统复杂,其中大兴断层是中西部的控盆边界断层,它通过对凹陷的构造样式、沉积特征的控制进而影响整个凹陷的油气分布。从区域构造背景和盆地的沉积演化角度,按不同段落断裂展布的方向、产状的陡缓、对沉积的控制作用以及不同层段物质组份的差异,将大兴断层划分为4段:北段、中北段、中南段和南段,各段又可进一步分为上下不同的两段。各段断层的结构、形态、伴生构造、活动时间等都存在较明显差异,通过控制物源而控制沉积相的展布、储层物性和生储盖组合。相应的伴生构造和沉积物发育特征导致构造、构造-岩性组合控制了油气的分布:北段下段、中北段下段近湖一侧是廊固凹陷中西部有利的油气聚集带;中北段上段发育的生物气藏具有一定的勘探前景。 相似文献
10.
A necessary and sufficient condition to test the robustness of a regulator of uncertain linear systems with constrained control is given. The candidate regulator for this test is that stabilizing nominal systems. An illustrative example is also given. 相似文献