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When travelling, people are accustomed to taking and uploading photos on social media websites, which has led to the accumulation of huge numbers of geotagged photos. Combined with multisource information (e.g. weather, transportation, or textual information), these geotagged photos could help us in constructing user preference profiles at a high level of detail. Therefore, using these geotagged photos, we built a personalised recommendation system to provide attraction recommendations that match a user's preferences. Specifically, we retrieved a geotagged photo collection from the public API for Flickr (Flickr.com) and fetched a large amount of other contextual information to rebuild a user's travel history. We then created a model-based recommendation method with a two-stage architecture that consists of candidate generation (the matching process) and candidate ranking. In the matching process, we used a support vector machine model that was modified for multiclass classification to generate the candidate list. In addition, we used a gradient boosting regression tree to score each candidate and rerank the list. Finally, we evaluated our recommendation results with respect to accuracy and ranking ability. Compared with widely used memory-based methods, our proposed method performs significantly better in the cold-start situation and when mining ‘long-tail’ data. 相似文献
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Model-free estimation from spatial samples: A reappraisal of classical sampling theory 总被引：1，自引：0，他引：1
A commonly held view among geostatisticians is that classical sampling theory is inapplicable to spatial sampling because spatial data are dependent, whereas classical sampling theory requires them to be independent. By comparing the assumptions and use of classical sampling theory with those of geostatistical theory, we conclude that this view is both false and unfortunate. In particular, estimates of spatial means based on classical sampling designs require fewer assumptions for their validity, and are therefore more robust, than those based on a geostatistical model. 相似文献
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土壤水分不仅在地表水、能量以及碳循环中发挥着非常重要的作用,其时空变化也是影响和反映气候变化的关键因子。虽然被动微波遥感技术是目前监测大尺度范围土壤水分变化最为成熟的技术手段,但是其土壤水分产品空间分辨率往往较低（几十千米不等）,不能满足区域和局地尺度的应用需求。鉴于这一问题,空间降尺度逐渐成为了提高被动微波土壤水分遥感产品空间分辨率的主要方式,也是当前遥感研究领域的热点之一。本文总结与分析了近20多年来国内外被动微波土壤水分遥感产品空间降尺度研究进展,系统归纳了经验性、半经验性和基于物理机理的3大类降尺度方法,并就各方法特征进行了详细说明,概述了各方法的优势和缺点。归纳而言,虽然被动微波土壤水分遥感产品空间降尺度方法众多,但可靠的高分辨率降尺度土壤水分产品仍较少,这与被动微波土壤水分遥感产品、降尺度关系模型方法以及降尺度辅助因子等有着直接的关联。未来相关研究应重点结合多源遥感数据建立适用性强、精度高的降尺度关系模型,进而实现时空无缝的高时空分辨率降尺度土壤水分产品的生产,为推动土壤水分遥感产品在农林业管理、自然灾害监测、水文过程分析等区域应用中提供支持。 相似文献
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Two fundamentally different sources of randomness exist on which design and inference in spatial sampling can be based: (a) variation that would occur on resampling the same spatial population with other sampling configurations generated by the same design, and (b) variation occurring on sampling other populations, hypothetically generated by the same spatial model, using the same sampling configuration. The former leads to the design-based approach, which uses classical sampling theory; the latter leads to the model-based approach and uses geostatistical theory. Failure to recognize these two sources of randomness causes misunderstanding about dependence of variables and the role of randomization in sampling, unwarranted narrowing down the choice of sampling strategies to those that are model-based, and abuse in simulation experiments. This is exemplified in Barnes' publication on the required sample size for geologic site characterization by nonparametric tolerance intervals. A basic design-based strategy like Simple Random Sampling is shown to require smaller sample sizes than the model-based strategy advocated by Barnes. In addition, Simple Random Sampling is completely robust against model errors and less complicated. 相似文献
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AbstractThis work presents a mapping and tracking system based on images to enable a small Unmanned Aerial Vehicle (UAV) to accurately navigate in indoor and GPS-denied outdoor environments. A method is proposed to estimate the UAV’s pose (i.e., the 3D position and orientation of the camera sensor) in real-time using only the on-board RGB camera as the UAV travels through a known 3D environment (i.e., a 3D CAD model). Linear features are extracted and automatically matched between images collected by the UAV’s onboard RGB camera and the 3D object model. The matched lines from the 3D model serve as ground control to estimate the camera pose in real-time via line-based space resection. The results demonstrate that the proposed model-based pose estimation algorithm provides sub-meter positioning accuracies in both indoor and outdoor environments. It is also that shown the proposed method can provide sparse updates to correct the drift from complementary simultaneous localization and mapping (SLAM)-derived pose estimates. 相似文献
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Edward R. Valstar Rob G. H. H. Nelissen Johan H. C. Reiber Piet M. Rozing 《ISPRS Journal of Photogrammetry and Remote Sensing》2002,56(5-6)
Roentgen stereophotogrammetry is the most accurate Roentgen technique for three-dimensional assessment of micromotion of orthopaedic implants. The reported accuracy of Roentgen Stereophotogrammetric Analysis (RSA) ranges between 0.05 and 0.5 mm for translations and between 0.15° and 1.15° for rotations. Because of the high accuracy of RSA, small patient groups are in general sufficient to study the effect on prosthetic fixation due to changes in implant design, addition of coatings, or new bone cements. By assessing micromotion of a prosthesis in a short-term (i.e. 2 years) clinical RSA study, a prediction can be made on the chance of long-term (i.e. 10 years) loosening of the prosthesis. Therefore, RSA is an important measurement tool to screen new developments in prosthetic design, and to prevent large groups of patients from being exposed to potentially inferior designs.In this article, the basics of the RSA technique are explained, and the importance of clinical RSA studies is illustrated with two examples of clinical RSA studies which RSA delivered very valuable information. Thereafter, two recent developments in RSA that have been implemented at Leiden University Medical Center are presented: digital automated measurements in RSA radiographs and model-based RSA. 相似文献
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介绍了原始极化SAR三分量分解中存在的问题,如负功率和散射机制模糊,并深入分析了其改进方法中仍然存在的缺陷,提出了一种自适应的三分量分解。该分解采用了更一般化的散射模型,并首次考虑了像素中存在不同旋转角的两个面或偶次散射目标,然后利用散射Alpha角确定除体散射之外的剩余主导散射机制,使面或偶次散射得到了更充分的保持。最后,从散射模型与极化相干矩阵自适应匹配的角度出发,提出了一种对负功率进行自适应优化的措施,使得负功率像素个数大大减少,从而分解更加准确有效。试验结果表明,该分解所得结果更符合实际地物散射过程,能更好地解决基于模型的分解方法中存在的缺陷。 相似文献
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对了解地下构造和描绘地下油气分布来说,用地面地震勘探技术可以分辩15～30 m的地层.低分辨率和缺乏详细的速度信息会降低地面地震勘探的效果,在研究更薄细的油气储层和研究已研究过的老区时,我们要采用一些更先进的勘探技术,对储层进行更精确的预测和描绘.本文分析了 VSP、测井和地面地震勘探各自的优势、不足和局限,采用VSP方法,我们只能得到井周围一定空问内的丰富速度信息,而详细的速度模型可以极大地提高地面地震勘探的效果.据此分析,组合VSP和地面地震方法优势的井-地观测系统(3D VSP),可有效地增加信息量,并可通过引入VSP数据处理时所用的基于模型的处理技术,来使井-地观测系统的优势进一步扩大,在此基础上,如果与精细测井相结合,可以更好的寻找和开发剩余油气,这将是我们今后重要的发展方向. 相似文献
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