Results 31 to 40 of about 37,022,143 (186)
Relevance feedback and intelligent technologies in content-based image retrieval system for medical applications [PDF]
, 2004 Relevance feedback has gained much interest from researchers in the discipline of content-based image retrieval (CBIR). However, such approach is rarely used in the content-based medical image retrieval (CBMIR) systems.
Fung, C.C., Chung, K.P.
core
Content based image retrieval by combining features and query-by-sketch [PDF]
This paper reports an approach to improve content-based image retrieval systems. Most current systems are based on a single technique for feature extraction and similarity search.
Lu, Joan, Pein, Raoul Pascal
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Automatic texture segmentation for content-based image retrieval application [PDF]
, 2006 In this article, a brief review on texture segmentation is presented, before a novel automatic texture segmentation algorithm is developed. The algorithm is based on a modified discrete wavelet frames and the mean shift algorithm.
Fauzi, M.F.A., Lewis, P.H.
core +2 more sources
Interactive Content Based Image Retrieval using Multiuser Feedback
JOIV: International Journal on Informatics Visualization, 2017 Retrieving images from large databases becomes a difficult task. Content based image retrieval (CBIR) deals with retrieval of images based on their similarities in content (features) between the query image and the target image.
M. Premkumar, R. Sowmya
doaj +1 more source
Content-Based Image Retrieval System
Ubiquity, 2008 The term CBIR seems to have originated in 1992, when it was describe experiments into automatic retrieval of images from a database, based on the colors and shapes present. Since then, the term has been used to describe the process of retrieving desired images from a large collection on the basis of syntactical image features. The techniques, tools and
Murari Mohan Sardar +2 more
openaire +1 more source
Content‐based image retrieval system via sparse representation
IET Computer Vision, 2016 The aim of image retrieval systems is to automatically assess, retrieve and represent relative images‐based user demand. However, the accuracy and speed of image retrieval are still an interesting topic of many researches.
Sajad Mohamadzadeh, Hassan Farsi
doaj +1 more source
Ontology of Gaps in Content-Based Image Retrieval [PDF]
Journal of Digital Imaging, 2008 Content-based image retrieval (CBIR) is a promising technology to enrich the core functionality of picture archiving and communication systems (PACS). CBIR has a potential for making a strong impact in diagnostics, research, and education. Research as reported in the scientific literature, however, has not made significant inroads as medical CBIR ...
Thomas Martin Deserno +2 more
openaire +3 more sources
Multi modal multi-semantic image retrieval [PDF]
, 2010 PhDThe rapid growth in the volume of visual information, e.g. image, and video can overwhelm users’ ability to find and access the specific visual information of interest to them.
Kesorn, Kraisak
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IEEE Access, 2022 With the rapid advancement of medical imaging technologies, the high-resolution CT image data is becoming increasingly valuable for both medical research and clinical diagnosis. The paper takes lung CT image as an example.
Yi Zhuang, Nan Jiang, Shuai Chen
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A co-occurrence region based Bayesian network stepwise remote sensing image retrieval algorithm
Earth Sciences Research Journal, 2018 Although scholars have conducted numerous researches on content-based image retrieval and obtained great achievements, they make little progress in studying remote sensing image retrieval. Both theoretical and application systems are immature.
Rui Zeng, Yingyan Wang, Wanliang Wang
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