8801.
稀疏矩阵向量乘（SpMV）是一种重要的数值线性代数运算,现有的优化存在预处理及通信时间考虑不全面、存储结构不具有普适性等问题。为了解决这些问题,提出异构平台下SpMV的自适应优化方案。所提方案利用皮尔逊相关系数确定相关度高的特征参数,并使用基于梯度提升决策树（GBDT）的极端梯度… … 相似文献
李博;黄建强;黄东强;王晓英 《计算机应用》2024,(12):3867-3875
8802.
随着大语言模型（LLM）在金融领域的应用潜力不断显现;评估金融大模型的性能变得尤为重要。然而;由于当下的金融评估方法评估任务单一、评测数据集覆盖面不足以及测评基准数据污染等方面的局限;大模型在金融领域的潜力尚未得到充分探索。基于此;提出了中文金融大模型评估方法CFB;构建36个数… … 相似文献
《计算机科学与探索》2024,18(12)
8803.
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信息超材料是一种人工结构阵列,其能够通过设计单元参数的排列方式定制等效材料和媒质属性,实现对电磁场和电磁波的灵活调控,带来全新的物理现象.基于信息超材料孔径的微波计算成像（Microwave Computational Imaging based Information Meta… … 相似文献
史洪印;彭毓晗;温裕广;黎芳;刘慧 《电子学报》2024,52(12):4048-4058
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8806.
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8808.
数据订正是资料同化的核心过程之一,即通过修正和校准数据提高资料同化的效果。针对气象观测存在多种误差导致气象数据存在偏差的问题,综述深度学习在气象数据订正中的应用,应用场景包括气象模式订正、天气预报和气候预测。首先,介绍气象数据订正的重要性,同时回顾传统的气象数据订正方法,如统计学… … 相似文献
8809.
ObjectiveTexture shows different characteristics on different scales. On a smaller scale, the texture may appear more intricate and detailed, but on a larger scale, texture may present large structures and patterns. Therefore, texture patterns are complex and diverse and show various characteristics across patterns. For example, structural texture has clear geometric shape and arrangement, natural texture has randomness and complexity, and abstract texture presents a combination of different colors, lines, and patterns. While the human visual system can effectively distinguish an ordered structure from a disordered one, computers are generally unable to do so. Texture filtering is a basic and important tool in the fields of computer vision and computer graphics whose main purpose is to filter out unnecessary texture details and maintain the stability of the core structure. The mainstream texture filtering methods are mainly divided into local- and global-based methods. However, the existing texture filtering methods do not effectively guarantee the structural stability while filtering the texture. To address this problem, we propose an adaptive regularization of the weighted relative total variation for image smoothing algorithm.MethodThe main idea of this algorithm is to obtain a structure measure amplitude image with high texture structure discrimination and then use the relative total variation model to smooth this image according to the difference between the texture and structure. Our method implements texture filtering and structure preservation in three steps. First, we propose a multi-scale interval circular gradient operator that can effectively distinguish texture from structure. By inputting the intensity change information of the interval gradient in the horizontal and vertical directions （captured by the interval circular gradient operator） into the frame of directional anisotropic structure measurement （DASM）, we generate a structure measure amplitude image with high contrast. In each iteration, we constantly adjust the scale radius of the interval circular gradient operator, where the scale radius of the interval circular gradient operator decreases as the number of iterations increases. On the one hand, this approach can capture the low-level semantic information of the texture structure in a large range at the initial stage of iteration and suppress the texture effectively. On the other hand, this approach can accurately capture the advanced semantic information of the texture structure at the end of the iteration to keep the structure stable. Second, given the high accuracy of the Gaussian mixture model in data classification, we separate the texture and structure layers of the structure measure amplitude image by using this model along with the EM algorithm. Before the separation operation, we conduct a morphological erosion operation on the image to refine the structure edge and shrink the structure area so as to improve the accuracy of the separation result. Finally, we adaptively assign regularization weights according to the structure measure amplitude image and the texture structure separation image. We assign a regularization term with high weight to the texture region for texture suppression, and we allocate a regularization term with a small weight in the structure area to maintain the stability of the fine structure and to ensure that the texture is filtered out in a large area to the greatest extent while maintaining the integrity of the structure.ResultWe ran our experiment on the Windows platform and implement our algorithm using Opencv and MATLAB. We defined three main parameters, including the maximum scale radius of the multi-scale interval circular gradient operator, the regular term of the texture region, and the regular term of the structure region. Maximum scale radius controls how much texture is suppressed. A larger regular term of the texture region corresponds to smoother filtering results, while a smaller regular term of the structure region corresponds to a better structure retention ability. On the visual level, by testing the images of oil paintings, cross embroideries, graffiti, murals, and natural scenes and comparing with the existing mainstream texture filtering methods, our proposed algorithm not only effectively suppresses the strong gradient texture but also maintains the stability of the edge of the weak gradient structure. In terms of quantitative measurement, by removing compressed traces of JPG images and smoothing Gaussian noise images, our proposed algorithm obtains the maximum peak signal-to-noise ratio （PSNR） and structural similarity index （SSIM） compared with the relative total variation, rolling guidance filtering, bilateral texture filtering, scale-aware texture filtering, and ![]()
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《中国图象图形学报》2024,29(12):3578-3594
8810.
ObjectiveCholangiocarcinoma is a type of cancer with high fatality rate, and the early detection and treatment of cancer can significantly r… … 相似文献
《中国图象图形学报》2024,29(12):3817-3832
8811.
8812.
8813.
8814.
借助于StyleGANs的解纠缠表示和多模态预训练模型中不同模态之间的语义对应关系,现有方法在跨模态风格迁移领域取得了较好的结果。然而,基于图像尺度分解的StyleGANs的潜在空间不利于局部属性的编辑,这会造成在迁移时对无关部分的干扰。该文提出细粒度文本引导的跨模态风格迁移模型… … 相似文献
孙世昶;魏爽;孟佳娜;林鸿飞;肖文浩;刘爽 《中文信息学报》2024,38(12):170-179
8815.
8816.
8817.
针对多智能体在大型仓储环境中进行路径规划时,现有算法有智能体易陷入拥堵区域和耗时长的问题,提出一种改良的基于冲突搜索（CBS）算法。首先,优化现有单一的仓储环境建模方式,在易解决路径冲突的传统的栅格化建模的基础上,提出栅格-热力图的混合建模方式,并通过热力图定位仓储中的拥堵区域,… … 相似文献
邓辅秦;谭朝恩;黎俊炜;钟家铭;付兰慧;张建民;王宏民;李楠楠;姜炳春;林天麟 《计算机应用》2024,(12):3854-3860
8818.
8819.
大模型是指拥有庞大参数量的深度学习模型,具备强大的表征学习和生成能力,对自然语言处理等领域产生了深远影响。随着技术的不断进步,大模型在性能和应用范围上不断取得突破,成为人工智能领域的研究热点。然而,大模型的发展也面临着一些挑战,如模型训练成本高、参数冗余以及跨语言应用存在局限性等… … 相似文献
杨毛加;柔特;才智杰;官却才让;贡去卓么 《中文信息学报》2024,38(12):106-115
8820.
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网站版权所有：中国科学院软件研究所 京ICP备09084417号-9
地址：北京海淀区中关村南四大街4号 邮编：100190 电话：010-62562563 E-mail ： cj_mail@jscas.ac.cn
本系统由:北京勤云科技发展有限公司提供技术支持
