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In nowadays, as the development of digital photographic technology, video files grow rapidly, there is a great demand for automatic video semantic analysis in many scenes, such as video semantic understanding, content-based analysis, video retrieval. Shot boundary detection is a key basic technology and first step for video analysis. However, recent methods are time consuming and performs bad in the...
We study efficient computation of Minimax distances measures, which enable to capture the correct structures via taking the transitive relations into account. We analyze in detail two settings, the dense graphs and the sparse graphs. In particular, we show that an adapted variant of the Kruskal’s algorithm is the most efficient approach for computing pairwise Minimax distances. However, for dense...
In this work, we report an ongoing study that aims to apply cluster validation measures for analyzing email communications at an organizational level of a company. This analysis can be used to evaluate the company structure and to produce further recommendations for structural improvements. Our initial evaluations, based on data in the forms of emails logs and organizational structure for a large...
This paper presents a method for assess the risk index in a power transformers park, risk index is a metric that allows park administrator to ensure an optimal physical asset management, allocating properly financial and human resources in operation and maintenance actions. Assessing risk index requires calculating two secondary sub-index termed failure probability and consequence factor. Those indexes...
Semantic similarity of texts is one of the important areas of Natural Language Processing, and there are several approaches to measure similarity: statistical, WordNet based, and hybrid. For all of these approaches, a lexical knowledge is used such as corpus or semantic network. WordNet is one of the most preferred and mature lexical knowledge base. In this study, we have focused on measuring semantic...
Relevance plays a key role in determining how ranking features are weighed in rank algorithms. In particular, the Search Engine Result Page (SERP) presents documents from the algorithmic relevance perspective. User relevance, however, is situational and describes the searcher's perception of the contextual document which is interpreted at rank time. Therefore, without it the monotonic decreasing click...
In this paper, the problem of single-channel blind source separation (SCBSS) of a mixture of two co-frequency phase-shift keying (PSK) signals with unknown carrier frequency offsets (CFOs) is investigated. Two SCBSS algorithms which are robust to CFOs are proposed to perform separation of the mixture signals. In the first algorithm, the phase changes of the received signals caused by CFOs are tracked...
Heap overflow is one of the most widely exploited vulnerabilities, with a large number of heap overflow instances reported every year. It is important to decide whether a crash caused by heap overflow can be turned into an exploit. Efficient and effective assessment of exploitability of crashes facilitates to identify severe vulnerabilities and thus prioritize resources. In this paper, we propose...
Link prediction plays an important role in complex network analysis. It is to predict the existence of an unknown link or a future link in a network. Classical methods for link prediction evaluate the similarity of vertices based on common neighbors, and denote that every common neighbor makes equal contribution to the connection likelihood. However, common neighbors may play different roles depending...
As an emissive display, the organic light emitting diode (OLED) endure an indispensable role on the market growth of consumer electronics. Despite the preferable power efficiency, the active matrix OLED (AMOLED) displays still consume large energy. To adaptively increase the power efficiency of AMOLED displays, we propose an adjustable pixel dimming algorithm based on the structural similarity metric...
A low-complexity algorithm is presented that clusters sensor nodes based on similarity in the sensed signals. This feature makes it an enabler for distributed detection of events that are impossible to identify using information available to a single node. The algorithm does not require system training prior to deployment nor does it assume statistical knowledge of the signal. Experimental results...
This paper presents the application of the Anisotropic Fast Marching Method to the path planning problem of robots moving in spatial environments. The slope of a terrain should be considered in a tensorial way because at any point on a mountainside there are two main slopes: the maximum, which is the slope of the gradient, and the minimum, which is the perpendicular slope to the gradient. The resulting...
Fragmentation in Elastic Optical Networks is an issue caused by isolated, non-aligned, and non-contiguous frequency slots that can not be used to allocate new connection request to the network, due to the optical layer restrictions imposed to the Routing and Spectrum Assignment (RSA) algorithms. To deal with this issue, several studies about Spectrum Defragmentation have been presented. In this work,...
This paper presents the details of a CUDA implementation of the Subgraph Isomorphism Graph Challenge, a new effort aimed at driving progress in the graph analytics field. challenge consists of two graph analytics: triangle counting and k-truss. We present our CUDA implementation of the graph triangle counting operation and of the k-truss subgraph decomposition. Both implementations share the same...
The number of extracted features for fault diagnosis in rotating machinery can grow considerably due to the large amount of available data collected from different monitored signals. Usually, feature selection or reduction are conducted through several techniques proposing a unique set of representative features for all available classes; nevertheless, in feature selection, it has been recognized...
The ability to discover patterns of interest in criminal networks can support and ease the investigation tasks by security and law enforcement agencies. By considering criminal networks as a special case of social networks, we can properly reuse most of the state-of-the-art techniques to discover patterns of interests, i.e., hidden and potential links. Nevertheless, in time-sensible scenarios, like...
Image blurriness or definition is an important indicator to assess the quality of digital image. The objective no-reference image blur metric plays significant roles in the design and optimization of visual perception-based auto-focus systems as well as image acquisition, transmission, enhancement, restoration and compression algorithms. In this paper, we proposed a novel no-reference image blur metric...
The research focus of designing local patch descriptors has gradually shifted from handcrafted ones (e.g., SIFT) to learned ones. In this paper, we propose to learn high performance descriptor in Euclidean space via the Convolutional Neural Network (CNN). Our method is distinctive in four aspects: (i) We propose a progressive sampling strategy which enables the network to access billions of training...
In this paper, we propose a consistent-aware deep learning (CADL) framework for person re-identification in a camera network. Unlike most existing person re-identification methods which identify whether two body images are from the same person, our approach aims to obtain the maximal correct matches for the whole camera network. Different from recently proposed camera network based re-identification...
Low resolution satellite products are often validated by point-scale in-situ soil moisture measurements from TDR/FDR devices, where the scale mismatch limits the quality of validation efforts in heterogeneous regions. In Cosmic Ray Neutron Probes (CRNP) provide area-average soil moisture within a 150–250 m radius footprint, so that they are able to fill the scale gap between both systems. In this...
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