Search Results - subject:"image retrieval"

Variants, meta-heuristic solution approaches and applications for image retrieval in business : comprehensive review and framework

Umamaheswaran, S.; Gabesh, K.; Suresh Kumar, N.; … - In: International journal of business information systems : … 18 (2015) 2, pp. 160-197

Persistent link: https://www.econbiz.de/10011326607

Image retrieval with textual label similarity features

Sagae, Alicia; Fahlman, Scott E. - In: Intelligent systems in accounting finance and … 22 (2015) 1, pp. 101-113

Persistent link: https://www.econbiz.de/10011402878

How do healthcare professionals select the medical images they need?

Sedghi, Shahram; Sanderson, Mark; Clough, Paul - In: Aslib Proceedings 65 (2013) 1, pp. 54-72

Purpose – The purpose of this paper is to investigate how healthcare professionals search for and select the medical images they need within medical settings. Design/methodology/approach – In total, 29 healthcare professionals participated in the study. Using a think‐aloud technique and...

Persistent link: https://www.econbiz.de/10014671736

How do health care professionals select medical images they need?

Sedghi, Shahram; Sanderson, Mark; Clough, Paul - In: Aslib Proceedings 64 (2012) 4, pp. 437-456

professionals is also vital to the design process and development of medical image retrieval systems. …

Persistent link: https://www.econbiz.de/10014671720

Scenery image retrieval by meta‐feature representation

Tsai, Chih‐Fong; Lin, Wei‐Chao - In: Online Information Review 36 (2012) 4, pp. 517-533

Purpose – Content‐based image retrieval suffers from the semantic gap problem: that images are represented by low … representation method for scenery image retrieval. In particular some class‐specific distances (namely meta‐features) between low … distinguishing a large number of conceptual categories for scenery image retrieval. In addition the meta‐features can be directly …

Persistent link: https://www.econbiz.de/10014966182

Medical image resources used by health care professionals

Sedghi, Shahram; Sanderson, Mark; Clough, Paul - In: Aslib Proceedings 63 (2011) 6, pp. 570-585

professionals is also vital to the design process and development of medical image retrieval systems. …

Persistent link: https://www.econbiz.de/10014671690

Facets of user‐assigned tags and their effectiveness in image retrieval

Ransom, Nicola; Rafferty, Pauline - In: Journal of Documentation 67 (2011) 6, pp. 1038-1066

Purpose – This study aims to consider the value of user‐assigned image tags by comparing the facets that are represented in image tags with those that are present in image queries to see if there is a similarity in the way that users describe and search for images....

Persistent link: https://www.econbiz.de/10014853521

A NEW METHOD OF MEDICAL IMAGE RETRIEVAL BASED ON COLOR–TEXTURE CORRELOGRAM AND GTI MODEL

TAI, XIAO-YING; WANG, LI-DONG; CHEN, QIN; FUJI, REN; … - In: International Journal of Information Technology & … 08 (2009) 02, pp. 239-248

This paper presents a method for endoscopic image retrieval based on color–texture correlogram and Generalized Tversky … image retrieval, GTI model is used in medical image retrieval for similarity metric, and the technique of relevance feedback …

Persistent link: https://www.econbiz.de/10004983223

FUZZY ART-BASED IMAGE CLUSTERING METHOD FOR CONTENT-BASED IMAGE RETRIEVAL

PARK, SANG-SUNG; SEO, KWANG-KYU; JANG, DONG-SIK - In: International Journal of Information Technology & … 06 (2007) 02, pp. 213-233

In this paper, an image clustering method that is essential for content-based image retrieval in large image databases …

Persistent link: https://www.econbiz.de/10004977390

Knowledge Augmented Medical Image Retrieval System

Shieh, Yao; Shieh, Mengkai; Chang, Chien-Hung; Lee, … - ToKnowPress

purpose of this paper is to demonstrate by presenting a concrete example that a knowledge augmented medical image retrieval …

Persistent link: https://www.econbiz.de/10010684237