scholarly journals The Effect of Candidate Image, Advertising, Program, and Party, toward Candidate Election Decision

2015 ◽  
Author(s):  
Julina Julina ◽  
Diana Eravia ◽  
Qomariah Qomariah
Keyword(s):  
Candidate Image

scholarly journals Enhancing ultrasound texture differences for developing an in vivo 'virtual histology' approach to bovine ovarian imaging

2007 ◽  
Vol 19 (8) ◽  
pp. 910 ◽  
Author(s):  
Mark G. Eramian ◽  
Gregg P. Adams ◽  
Roger A. Pierson
Keyword(s):  
Image Processing ◽  
Ultrasound Image ◽  
Ultrasound Images ◽  
Virtual Histology ◽  
Form And Function ◽  
Non Invasive ◽  
Candidate Image ◽  
And Function ◽  
Processing Techniques

A ‘virtual histology’ can be thought of as the ‘staining’ of a digital ultrasound image via image processing techniques in order to enhance the visualisation of differences in the echotexture of different types of tissues. Several candidate image-processing algorithms for virtual histology using ultrasound images of the bovine ovary were studied. The candidate algorithms were evaluated qualitatively for the ability to enhance the visual differences in intra-ovarian structures and quantitatively, using standard texture description features, for the ability to increase statistical differences in the echotexture of different ovarian tissues. Certain algorithms were found to create textures that were representative of ovarian micro-anatomical structures that one would observe in actual histology. Quantitative analysis using standard texture description features showed that our algorithms increased the statistical differences in the echotexture of stroma regions and corpus luteum regions. This work represents a first step toward both a general algorithm for the virtual histology of ultrasound images and understanding dynamic changes in form and function of the ovary at the microscopic level in a safe, repeatable and non-invasive way.

scholarly journals Shape Similarity Measurement for Known-Object Localization: A New Normalized Assessment

2019 ◽  
Vol 5 (10) ◽  
pp. 77
Author(s):  
Baptiste Magnier ◽  
Behrang Moradi
Keyword(s):  
Shape Matching ◽  
Performance Measure ◽  
Object Localization ◽  
Similarity Measurement ◽  
Shape Similarity ◽  
Image Normalization ◽  
Object Shape ◽  
Binary Images ◽  
Candidate Image ◽  
Matching Estimation

This paper presents a new, normalized measure for assessing a contour-based object pose. Regarding binary images, the algorithm enables supervised assessment of known-object recognition and localization. A performance measure is computed to quantify differences between a reference edge map and a candidate image. Normalization is appropriate for interpreting the result of the pose assessment. Furthermore, the new measure is well motivated by highlighting the limitations of existing metrics to the main shape variations (translation, rotation, and scaling), by showing how the proposed measure is more robust to them. Indeed, this measure can determine to what extent an object shape differs from a desired position. In comparison with 6 other approaches, experiments performed on real images at different sizes/scales demonstrate the suitability of the new method for object-pose or shape-matching estimation.

Hillary Through TIME: The (Un)Making of the First Woman President

2017 ◽  
Vol 63 (7) ◽  
pp. 807-825 ◽  
Author(s):  
Mary Anne Taylor ◽  
Danee Pye
Keyword(s):  
Visual Rhetoric ◽  
Status Quo ◽  
Cover Image ◽  
Time Magazine ◽  
First Lady ◽  
Executive Leaders ◽  
American Presidency ◽  
Image Construction ◽  
Candidate Image ◽  
Semiotic Approach

This essay critically examines Hillary Clinton’s (Hillary) TIME Magazine coverage, from the first cover image as a First Lady in 1992, to the most recent cover as a 2016 presidential hopeful, and each of the focal images throughout TIME’s 20-year coverage. Drawing from political and visual rhetoric as a primary lens, the analysis of each cover will investigate two primary texts: Hillary’s image as coded by a social semiotic approach and the editorial reporting of TIME’s senior writers. Each of Hillary’s cover appearances and corresponding articles are then rhetorically analyzed with a focus on how her mediated image is perpetuated as a threat to political hegemony. Through these themes, we argue that the reporting and image construction of Hillary reinforces normative and status quo-journalism, and ultimately celebrates Hillary as a diplomat, senator, and wife, while disciplining her candidate image as a threat to the American presidency. After a thoughtful dialogue about each cover and the broader implications for political women as executive leaders, this article ultimately advances an argument for a new epistemological and ideological understanding of reporting for political women.

Post-Debate Analysis and Media Reliance: Influences on Candidate Image and Voting Probabilities

1993 ◽  
Vol 70 (2) ◽  
pp. 321-335 ◽  
Author(s):  
William R. Elliott ◽  
Jayanthi Sothirajah
Keyword(s):  
Television News ◽  
Presidential Candidate ◽  
Candidate Image

This study of 798 potential voters interviewed beginning three days before the September 25, 1988, presidential candidate debate and ending four days later analyzed the influence of exposure to television post-debate analysis and television and newspaper reliance on evaluations of candidate debate performance, candidate image, and voting preferences. Exposure to the debate and to post-debate television analysis had measurable and consistent influences on the evaluation of Dukakis as a debater (Dukakis was the consensus post-debate analysis winner), on Dukakis's image, and on the probability of voting for both candidates. Television news reliance for debate information was significantly related to debater ratings and the candidates' images for both candidates. There was a slight relationship between television news reliance and the probability of voting for Dukakis.

Candidate Image Attributes

1999 ◽  
Vol 26 (4) ◽  
pp. 414-428 ◽  
Author(s):  
SPIRO KIOUSIS ◽  
PHILEMON BANTIMAROUDIS ◽  
HYUN BAN
Keyword(s):  
Candidate Image

TRAVELOGUE ENRICHING AND SCENIC SPOT OVERVIEW BASED ON TEXTUAL AND VISUAL TOPIC MODELS

2011 ◽  
Vol 25 (03) ◽  
pp. 373-390 ◽  
Author(s):  
YANWEI PANG ◽  
XIN LU ◽  
YUAN YUAN ◽  
XUELONG LI
Keyword(s):  
Visual Information ◽  
Probabilistic Models ◽  
Layer Model ◽  
Comprehensive Overview ◽  
Image Layer ◽  
Scenic Spot ◽  
Candidate Image ◽  
Image Set ◽  
Web Images ◽  
Historical Sites

We consider the problem of enriching the travelogue associated with a small number (even one) of images with more web images. Images associated with the travelogue always consist of the content and the style of textual information. Relying on this assumption, in this paper, we present a framework of travelogue enriching, exploiting both textual and visual information generated by different users. The framework aims to select the most relevant images from automatically collected candidate image set to enrich the given travelogue, and form a comprehensive overview of the scenic spot. To do these, we propose to build two-layer probabilistic models, i.e. a text-layer model and image-layer models, on offline collected travelogues and images. Each topic (e.g. Sea, Mountain, Historical Sites) in the text-layer model is followed by an image-layer model with sub-topics learnt (e.g. the topic of sea is with the sub-topic like beach, tree, sunrise and sunset). Based on the model, we develop strategies to enrich travelogues in the following steps: (1) remove noisy names of scenic spots from travelogues; (2) generate queries to automatically gather candidate image set; (3) select images to enrich the travelogue; and (4) choose images to portray the visual content of a scenic spot. Experimental results on Chinese travelogues demonstrate the potential of the proposed approach on tasks of travelogue enrichment and the corresponding scenic spot illustration.

scholarly journals ENHANCED MULTIQUERY SYSTEM USING KNN FOR CONTENT BASED IMAGE RETRIEVAL

2017 ◽  
Vol 16 (1) ◽  
pp. 7515-7523
Author(s):  
Meenu Meenu ◽  
Sonika Jindal
Keyword(s):  
Image Retrieval ◽  
Multimedia Systems ◽  
Content Based Image Retrieval ◽  
Query Image ◽  
Storage Devices ◽  
Feature Vectors ◽  
Candidate Image ◽  
Image Set ◽  
Classification Of Images ◽  
Representative Image

Content Based Image Retrieval (CBIR) techniques are becoming an essential requirement in the multimedia systems with the widespread use of internet, declining cost of storage devices and the exponential growth of un-annotated digital image information available in recent years.  Therefore multi query systems have been used rather than a single query in order to bridge the semantic gaps and in order to understand user’s requirements. Moreover, query replacement algorithm has been used in the previous works in which user provides multiple images to the query image set referred as representative images. Feature vectors are extracted for each image in the representative image set and every image in the database. The centroid, Crep of the representative images is obtained by computing the mean of their feature vectors. Then every image in the representative image set is replaced with the same candidate image in the dataset one by one and new centroids are calculated for every replacement .The distance between each of the centroids resulting from the replacement and the representative image centroid Crep is calculated using Euclidean distance. The cumulative sum of these distances determines the similarity of the candidate image with the representative image set and is used for ranking the images. The smaller the distance, the similar will be the image with the representative image set. But it has some research gaps like it takes a lot of time to extract feature of each and every image from the database and compare our image with the database images and complexity as well as cost increases. So in our proposed work, the KNN algorithm is applied for classification of images in the database image set using the query images and the candidate images are reduced to images returned after classification mechanism which leads to decrease the execution time and reduce the number of iterations. Hence due to hybrid model of multi query and KNN, the effectiveness of image retrieval in CBIR system increases. The language used in this work is C /C++ with Open CV libraries and IDE is Visual studio 2015. The experimental results show that our method is more effective to improve the performance of the retrieval of images.

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