As different posture has different projection histogram pattern,. the projection histogram can be used as one of the features to discriminate different postures. In this paper, a new method using projection histogram ...
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ISBN:
(纸本)9780780397361
As different posture has different projection histogram pattern,. the projection histogram can be used as one of the features to discriminate different postures. In this paper, a new method using projection histogram for static human posture recognition is proposed. It comprises of three key modules: background subtraction, projection histogram computing and template matching. Comparing with many other methods, our approach is fast, simple and less sensitive to noise. Using our new method, a system is implemented and tested with ten static postures. It can automatically recognize them with high percentage of right decisions.
In this paper the author describes a new method, called string distance measurement (SDM), for recognizing handwritten characters. the advantage of this technique is that it can be applied in a generic manner to diffe...
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We investigate the reaction-diffusion system of the classical Bazykin model in spatial two dimensional domain. In this paper, we derive the conditions for turing instability in detail and obtain the turing space, in w...
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In our research we compare various neural network architectures that are used for object detection and recognition. In this work vehicles and pedestrians are considered objects of interest. Modern artificial neural ne...
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ISBN:
(纸本)9781728117393
In our research we compare various neural network architectures that are used for object detection and recognition. In this work vehicles and pedestrians are considered objects of interest. Modern artificial neural networks are able to detect and localize objects of known classes. this allows them to be used in various technical vision systems and video analysis systems. In this paper we compare three architectures (YOLO, Faster R-CNN, SSD) by the following criteria: processing speed, mAP, precision and recall.
the proceedings contain 164 papers. the topics discussed include: performance comparison of IEEE 802.1Q and IEEE 802.1 AVB in an Ethernet-based in-vehicle network;a fast seat assignment algorithm based-on bucket data ...
ISBN:
(纸本)9788988678671
the proceedings contain 164 papers. the topics discussed include: performance comparison of IEEE 802.1Q and IEEE 802.1 AVB in an Ethernet-based in-vehicle network;a fast seat assignment algorithm based-on bucket data structure;a two-phase iterative pre-copy strategy for live migration of virtual machines;an empirical evaluation and improvement of the item balancing algorithm in P2P systems;towards high performance and usability programming model for heterogeneous HPC platforms;saving streaming bandwidth via wireless sharing for a tree-based live streaming system on public-shared network;a novel pattern of distributed low-rate denial of service attack disrupts Internet routing;achieving maximum performance for matrix multiplication using set associative cache;a user context recognition method for ubiquitous computing systems;the influence factors to the enterprise microblogs - a research of the restaurant enterprise microblogs on ***;and common-sense reasoning in constructive discursive logic.
As cloud based platforms become more popular, it becomes an essential task for the cloud administrator to efficiently manage the costly hardware resources in the cloud environment. Prompt action should be taken whenev...
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ISBN:
(纸本)9781509014453
As cloud based platforms become more popular, it becomes an essential task for the cloud administrator to efficiently manage the costly hardware resources in the cloud environment. Prompt action should be taken whenever hardware resources are faulty, or configured and utilized in a way that causes application performance degradation, hence poor quality of service. In this paper, we propose a semantic aware technique based on neural network learning and patternrecognition in order to provide automated, real-time support for resource anomaly detection. We incorporate application semantics to narrow down the scope of the learning and detection phase, thus enabling our machine learning technique to work at a very low overhead when executed online. As our method runs "life-long" on monitored resource usage on the cloud, in case of wrong prediction, we can leverage administrator feedback to improve prediction on future runs. this feedback directed scheme withthe attached context helps us to achieve an anomaly detection accuracy of as high as 98.3% in our experimental evaluation, and can be easily used in conjunction with other anomaly detection techniques for the cloud.
Data is being generated very rapidly and at very high magnitudes. this data, termed as 'Big Data has found its use in many fields. the aim of this paper is to discuss the challenges posed by Big Data analysis and ...
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ISBN:
(纸本)9781538617199
Data is being generated very rapidly and at very high magnitudes. this data, termed as 'Big Data has found its use in many fields. the aim of this paper is to discuss the challenges posed by Big Data analysis and the techniques that can he used to solve these challenges. One of the most efficient techniques used to do so is Deep Learning. this paper also focuses on the models that have been implemented for big data analysis with deep learning and its applications.
the proceedings contain 164 papers. the topics discussed include: performance comparison of IEEE 802.1Q and IEEE 802.1 AVB in an Ethernet-based in-vehicle network;a fast seat assignment algorithm based-on bucket data ...
ISBN:
(纸本)9788988678671
the proceedings contain 164 papers. the topics discussed include: performance comparison of IEEE 802.1Q and IEEE 802.1 AVB in an Ethernet-based in-vehicle network;a fast seat assignment algorithm based-on bucket data structure;a two-phase iterative pre-copy strategy for live migration of virtual machines;an empirical evaluation and improvement of the item balancing algorithm in P2P systems;towards high performance and usability programming model for heterogeneous HPC platforms;saving streaming bandwidth via wireless sharing for a tree-based live streaming system on public-shared network;a novel pattern of distributed low-rate denial of service attack disrupts Internet routing;achieving maximum performance for matrix multiplication using set associative cache;a user context recognition method for ubiquitous computing systems;the influence factors to the enterprise microblogs - a research of the restaurant enterprise microblogs on ***;and common-sense reasoning in constructive discursive logic.
Web mining uses data mining's techniques and its algorithms to explore the interesting patterns from the web access log on server data to withdraw out better knowledge of user attractions or users activity over th...
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ISBN:
(纸本)9781538617199
Web mining uses data mining's techniques and its algorithms to explore the interesting patterns from the web access log on server data to withdraw out better knowledge of user attractions or users activity over the website. this paper gives the idea that how an industry conclude or examine their user's behavior on their websites, which is one of the important topics in today's time using the time stamp of the IP address. this paper deals withthe temporal approach of weblog mining on NASA's website based on temporal trend analysis by analyzing the extracted interesting patterns. A weblog of NASA has been analyzed using R-Studio to extract the trend pattern based on the time of stay of users, which creates a particular pattern. there are many methods for data mining extractions, but this technique of trend analysis can provide more useful information for web mining.
Identifying the pattern support distribution (PSD) in datasets is useful for many data mining tasks, such as market basket analysis. the support of a pattern is the frequency of its occurrence in a dataset. Calculatin...
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ISBN:
(纸本)9780769532424
Identifying the pattern support distribution (PSD) in datasets is useful for many data mining tasks, such as market basket analysis. the support of a pattern is the frequency of its occurrence in a dataset. Calculating the distribution of these supports over an entire dataset is computationally expensive;this cost can be reduced by sampling from the dataset and computingthe PSD on a relatively small sample. However, this may miscount patterns and cause significant changes in the distribution identified. Based on the fact that the PSD shows a power-law relationship, in this paper we investigate the influence of sampling on the characteristics of the power-law relationship in the pattern support distribution. We consider sampling effect on this relationship under two assumptions: uniform distribution of pattern supports, and independent identically distributed (i.i.d.) distributions. We experimentally evaluate the influence on data from four real-world transaction datasets.
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