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Fast Object Localization via Sensitivity Analysis
2019Deep Convolutional Neural Networks (CNNs) have been repeatedly shown to perform well on image classification tasks, successfully recognizing a broad array of objects when given sufficient training data. Methods for object localization, however, are still in need of substantial improvement.
Mohammad K. Ebrahimpour, David C. Noelle
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A fatigue model with local sensitivity analysis
Fatigue & Fracture of Engineering Materials & Structures, 2007ABSTRACTThe goal of this paper is two fold. First, it introduces a general parametric lifetime model for high‐cycle fatigue regime derived from physical, statistical, engineering and dimensional analysis considerations. The proposed model has two threshold parameters and three Weibull distribution parameters.
E. CASTILLO +3 more
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Hoffman's Error Bound, Local Controllability, and Sensitivity Analysis
SIAM Journal on Control and Optimization, 2000Summary: Our aim is to present sufficient conditions ensuring Hoffman's error bound for lower semicontinuous nonconvex inequality systems and to analyze its impact on the local controllability, implicit function theorem for (non-Lipschitz) multivalued mappings, generalized equations (variational inequalities), and sensitivity analysis and on other ...
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Local Sensitive Frontier Analysis based facial expression recognition
2011 8th International Conference on Information, Communications & Signal Processing, 2011Facial expression recognition plays an important role in interactive entertainment. In this paper, LSFA (Local Sensitive Frontier Analysis) a novel feature extraction method is introduced for facial expression recognition. LSFA is designed as manifold based feature extraction method to obtain useful features from the facial expression pictures, since ...
null Chao Wang, null Zhiqi Shen
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Adjoint-Based Local Sensitivity Analysis
2018This chapter introduces the adjoint operator equations for local sensitivity analysis, an intrusive method for sensitivity analysis. Section 6.1 introduces the adjoint operator and demonstrates that for a somewhat general class of QoIs, a QoI can be written as an inner product of the adjoint equations.
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Local Sensitivity Analysis with Constraints
2017This chapter, which is our last on deterministic methods, addresses the removal of a typical assumption in sensitivity analysis.
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On The Local Sensitivity Analysis for Phase Expansion
2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S), 2021This paper presents the local sensitivity for phase expansion. The purpose of phase expansion is to determine the phase-type (PH) parameters to approximate the original distribution with the fitted PH distribution. Since PH parameters are estimated from the original distribution, whose parameters may contain estimation errors, it is important to ...
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Local Sensitivity Analysis and Matrix Derivatives
1982This paper discusses two types of matrix by matrix derivatives; the B-type derivative, introduced by Balestra (1976) and the new defined A-type derivative, because of the arrangement in a “anti-Kronecker” type fashion. Both types of derivatives are linked by permutation matrices (also called commutation matrices by Magnus & Neudecker (1979)), a special
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Geometric sensitivity analysis with local coordinate transformations
Communications in Applied Numerical Methods, 1988AbstractThe dimensionality of truss, beam, membrane and shell finite elements is often less than that of the global co‐ordinate system, and element calculations must be performed in local co‐ordinates. Design parameters which affect the nodal co‐ordinates in such elements control both the element dimensions and orientation, and element design ...
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A locally sensitive method for cluster analysis
Pattern Recognition, 1976Abstract In this paper a new method of mode separation is proposed. The method is based on mapping of data points from the N -dimensional space onto a sequence so that the majority of points from each mode become successive elements of the sequence. The intervals of points in the sequence belonging to the respective modes of the p.d.f.
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