Informative sequential selection of variable-sized patches for image retrieval

2017 ◽  
Author(s):  
Zhihao Shen ◽  
Hosun Lee ◽  
Sungmoon Jeong ◽  
Nak Young Chong
Keyword(s):  
Image Retrieval ◽  
Sequential Selection ◽  
Selection Of

scholarly journals Content Based Image Retrieval using Collaborative Color, Texture and Shape Features

2020 ◽  
Vol 9 (3) ◽  
pp. 1466-1469
Keyword(s):  
Feature Extraction ◽  
Image Retrieval ◽  
Texture Feature ◽  
Content Based Image Retrieval ◽  
Support Vector ◽  
Feature Extraction Method ◽  
Attribute Extraction ◽  
The Individual ◽  
Selection Of ◽  
Color Texture

Selection of feature extraction method is incredibly recondite task in Content Based Image Retrieval (CBIR). In this paper, CBIR is implemented using collaboration of color; texture and shape attribute to improve the feature discriminating property. The implementation is divided in to three steps such as preprocessing, features extraction, classification. We have proposed color histogram features for color feature extraction, Local Binary Pattern (LBP) for texture feature extraction, and Histogram of oriented gradients (HOG) for shape attribute extraction. For the classification support vector machine classifier is applied. Experimental results show that combination of all three features outperforms the individual feature or combination of two feature extraction techniques

Dynamic selection of classifiers for Content Based Image Retrieval

2021 ◽  
Author(s):  
Safa Hamreras ◽  
Bachir Boucheham ◽  
Miguel A. Molina-Cabello ◽  
Rafaela Benitez-Rochel ◽  
Ezequiel Lopez-Rubio
Keyword(s):  
Image Retrieval ◽  
Content Based Image Retrieval ◽  
Dynamic Selection ◽  
Selection Of

Estimation of Performance and Sequential Selection of Diagnostic Tests in Patients With Lung Lesions Suspicious for Cancer

2002 ◽  
Vol 126 (1) ◽  
pp. 19-27
Author(s):  
Dana Marie Grzybicki ◽  
Thomas Gross ◽  
Kim R. Geisinger ◽  
Stephen S. Raab
Keyword(s):  
Diagnostic Test ◽  
Test Performance ◽  
Diagnostic Tests ◽  
Needle Aspiration ◽  
Selection Strategy ◽  
Test Selection ◽  
Lung Lesions ◽  
Sequential Selection ◽  
Test Ordering ◽  
Selection Of

Abstract Context.—Measuring variation in clinician test ordering behavior for patients with similar indications is an important focus for quality management and cost containment. Objective.—To obtain information from physicians and nonphysicians regarding their test-ordering behavior and their knowledge of test performance characteristics for diagnostic tests used to work up patients with lung lesions suspicious for cancer. Design.—A self-administered, voluntary, anonymous questionnaire was distributed to 452 multiple-specialty physicians and 500 nonphysicians in academic and private practice in Pennsylvania, Iowa, and North Carolina. Respondents indicated their estimates of test sensitivities for multiple tests used in the diagnosis of lung lesions and provided their test selection strategy for case simulations of patients with solitary lung lesions. Data were analyzed using descriptive statistics and the χ2 test. Results.—The response rate was 11.2%. Both physicians and nonphysicians tended to underestimate the sensitivities of all minimally invasive tests, with the greatest underestimations reported for sputum cytology and transthoracic fine-needle aspiration biopsy. There was marked variation in sequential test selection for all the case simulations and no association between respondent perception of test sensitivity and their selection of first diagnostic test. Overall, the most frequently chosen first diagnostic test was bronchoscopy. Conclusions.—Physicians and nonphysicians tend to underestimate the performance of diagnostic tests used to evaluate solitary lung lesions. However, their misperceptions do not appear to explain the wide variation in test-ordering behavior for patients with lung lesions suspicious for cancer.

Optimized Image Retrieval System in Oracle DBMS

2017 ◽  
Vol 8 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Kaouther Zekri ◽  
Amel Grissa Touzi ◽  
Noureddine Ellouze
Keyword(s):  
Image Retrieval ◽  
Retrieval System ◽  
Similarity Criteria ◽  
Search Process ◽  
Textual Information ◽  
Experimental Part ◽  
Content Description ◽  
Image Retrieval System ◽  
Assistance Tool ◽  
Selection Of

In this work, the authors are moving towards the creation of an effective image retrieval system in Oracle DBMS. Several DBMSs have been extensively used to manage the textual information stored with images and CBIR tasks usually rely on specific applications. The separation between the DBMSs and CBIR prevents the optimization of integrated search process based on the connection between the textual and visual content description of image. Moreover, the relevance of image retrieval depends directly on the choice of similarity criteria (color, texture, shape) that can give inaccurate results in case of non-trivial selection of these parameters. The purpose of the authors' approach is to build a CBIR system using advanced and integrated retrieval techniques defined in Oracle DBMS. This approach provides an assistance tool that can guide the user to the appropriate choice of search criteria. The authors present an experimental part that measures the performance of their system, which can help the user to correctly model his query by giving the appropriate retrieval criteria for a database with 800 images.

Optimal Sequential selection of n random variables under a constraint

1984 ◽  
Vol 21 (03) ◽  
pp. 537-547 ◽  
Author(s):  
R. W. Chen ◽  
V. N. Nair ◽  
A. M. Odlyzko ◽  
L. A. Shepp ◽  
Y. Vardi
Keyword(s):  
Random Variables ◽  
Selection Procedure ◽  
Expected Number ◽  
Sequential Selection ◽  
Selection Of

We observe a sequence {Xk } k≧1 of i.i.d. non-negative random variables one at a time. After each observation, we select or reject the observed variable. A variable that is rejected may not be recalled. We want to select N variables as soon as possible subject to the constraint that the sum of the N selected variables does not exceed some prescribed value C > 0. In this paper, we develop a sequential selection procedure that minimizes the expected number of observed variables, and we study some of its properties. We also consider the situation where N → ∞and C/N → α > 0. Some applications are briefly discussed.

Sequential selection of random vectors under a sum constraint

2004 ◽  
Vol 41 (1) ◽  
pp. 131-146
Author(s):  
Mario Stanke
Keyword(s):  
Continuous Distribution ◽  
Center Of Gravity ◽  
Continuous Measure ◽  
Random Vectors ◽  
Expected Number ◽  
Absolutely Continuous ◽  
Selection Policy ◽  
Sequential Selection ◽  
Absolutely Continuous Measure ◽  
Selection Of

We observe a sequence X1, X2,…, Xn of independent and identically distributed coordinatewise nonnegative d-dimensional random vectors. When a vector is observed it can either be selected or rejected but once made this decision is final. In each coordinate the sum of the selected vectors must not exceed a given constant. The problem is to find a selection policy that maximizes the expected number of selected vectors. For a general absolutely continuous distribution of the Xi we determine the maximal expected number of selected vectors asymptotically and give a selection policy which asymptotically achieves optimality. This problem raises a question closely related to the following problem. Given an absolutely continuous measure μ on Q = [0,1]d and a τ ∈ Q, find a set A of maximal measure μ(A) among all A ⊂ Q whose center of gravity lies below τ in all coordinates. We will show that a simplicial section {x ∈ Q | 〈x, θ〉 ≤ 1}, where θ ∈ ℝd, θ ≥ 0, satisfies a certain additional property, is a solution to this problem.

Sequential selection of random vectors under a sum constraint

2004 ◽  
Vol 41 (01) ◽  
pp. 131-146
Author(s):  
Mario Stanke
Keyword(s):  
Continuous Distribution ◽  
Center Of Gravity ◽  
Continuous Measure ◽  
Random Vectors ◽  
Expected Number ◽  
Absolutely Continuous ◽  
Selection Policy ◽  
Sequential Selection ◽  
Absolutely Continuous Measure ◽  
Selection Of

We observe a sequence X 1, X 2,…, X n of independent and identically distributed coordinatewise nonnegative d-dimensional random vectors. When a vector is observed it can either be selected or rejected but once made this decision is final. In each coordinate the sum of the selected vectors must not exceed a given constant. The problem is to find a selection policy that maximizes the expected number of selected vectors. For a general absolutely continuous distribution of the X i we determine the maximal expected number of selected vectors asymptotically and give a selection policy which asymptotically achieves optimality. This problem raises a question closely related to the following problem. Given an absolutely continuous measure μ on Q = [0,1] d and a τ ∈ Q, find a set A of maximal measure μ(A) among all A ⊂ Q whose center of gravity lies below τ in all coordinates. We will show that a simplicial section { x ∈ Q | 〈 x , θ 〉 ≤ 1}, where θ ∈ ℝ d , θ ≥ 0, satisfies a certain additional property, is a solution to this problem.

scholarly journals Viewing team selection through a temporal lens

2017 ◽  
Vol 7 (2) ◽  
pp. 171-194 ◽  
Author(s):  
Jonathan Pinto
Keyword(s):  
Organizational Behavior ◽  
Membership Change ◽  
Research And Practice ◽  
Selection Processes ◽  
Team Selection ◽  
Sequential Selection ◽  
Selection Framework ◽  
Research Stream ◽  
Personnel Psychology ◽  
Selection Of

This paper builds synthesized coherence (Locke & Golden-Biddle, 1997) across disciplines such as organizational behavior, personnel psychology, entrepreneurship, project management, and strategic management by developing a temporal team selection framework that delineates three temporal team selection processes (i.e., simultaneous selection, sequential selection, and substitution selection). Of these three processes, sequential selection, which could either be constraint-driven or coevolution-driven, is a new conceptualization. This framework speaks to the broader research stream on membership dynamics, and therefore its key constructs such as arithmetic of membership change (Arrow & McGrath, 1993) and temporal patterning of membership change (Arrow & McGrath, 1993) have been systematically applied to the temporal team selection processes. Finally, the implications of this theorizing for both research and practice are discussed.

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