Results 231 to 240 of about 3,970,331 (279)

Common Seasonal Features: Global Unemployment

SSRN Electronic Journal, 1996
Seasonal patterns in economic time series are generally examined from a univariate point of view. Using extensions of the unit root literature, important classes of seasonal processes are deterministic, stationary stochastic or mean reverting, and unit root stochastic.
Engle, Robert F., Hylleberg, Svend
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Local and Global Feature Based Explainable Feature Envy Detection

2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), 2021
Code smell detection can help developers identify position of code smell in projects and enhance the quality of software system. Usually codes with similar semantic relationships have greater code dependencies, and most code smell detection methods ignore dependencies relationships within the source code.
Xin Yin, Chongyang Shi, Shuxin Zhao
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EEG Features in Transient Global Amnesia

Clinical Electroencephalography, 1987
Forty-seven patients with one or more episodes of transient global amnesia (TGA) were studied by means of standard and 24-hour ambulatory cassette recording electroencephalography (EEG). Only one individual, with a left frontal hemorrhage, had intracranial lesions. TGA was multiple in 16 of the patients (34%), the attacks recurring with an average time
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Analysis of global pattern features

Pattern Recognition, 1974
Abstract A fundamental method for analysing the global features of visual patterns is presented. Pattern features are considered to be synonomous with non-random distributions in the pattern statistics. In particular, the statistics of the chords of the patterns are considered, leading to the histograms of the chord lengths and angles. Peaks in these
D.J.H. Moore, D.J. Parker
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Action Recognition with Global Features

2005
In this study, a new method allowing recognizing and segmenting everyday life actions is proposed. Only one camera is utilized without calibration. Viewpoint invariance is obtained by several acquisitions of the same action. To enhance robustness, each sequence is characterized globally: a detection of moving areas is first computed on each image.
Mokhber, Arash, Achard, Catherine, Qu, Xingtai, Milgram, Maurice   +3 more
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Local-to-global semi-supervised feature selection

Proceedings of the 22nd ACM international conference on Information & Knowledge Management, 2013
Variable-weighting approaches are well-known in the context of embedded feature selection. Generally, this task is performed in a global way, when the algorithm selects a single cluster-independent subset of features (global feature selection). However, there exist other approaches that aim to select cluster-specific subsets of features (local feature ...
Hindawi, Mohammed, Benabdeslem, Khalid
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Global Value Chains: Key Features of Economic Globalization

SSRN Electronic Journal, 2016
Contemporary systems of production and distribution of goods and services are increasingly becoming incorporated into global value chains. This process has been strengthened since the end of the Cold War, as restrictions over communication, trade flows and finance have been diminishing by both technological improvements and the international political ...
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Inferring global pereeptual contours from local features

International Journal of Computer Vision, 1996
We address the problem of contour inference from partial data, as obtained from state-of-the-art edge detectors. We argue that in order to obtain more pereeptually salient contours, it is necessary to impose generic constraints such as continuity and co-curvilinearity.
G. Guy, G. Medioni
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Global Feature Guided Local Pooling

2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019
In deep convolutional neural networks (CNNs), local pooling operation is a key building block to effectively downsize feature maps for reducing computation cost as well as increasing robustness against input variation. There are several types of pooling operation, such as average/max-pooling, from which one has to be manually selected for building CNNs.
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