Results 11 to 20 of about 2,978 (220)

Comparative Study on Content-Based Image Retrieval (CBIR)

2012 International Conference on Advanced Computer Science Applications and Technologies (ACSAT), 2012
The process of retrieving desired images from a large collection is widely used in applications of computer vision. In order to improve the retrieval performance an efficient and accurate system is required. Retrieving images based on the content i.e. color, texture, shape etc is called content based image retrieval (CBIR).
Ayyaz Hussain
exaly   +3 more sources

Content Based Image Retrieval (CBIR) by Statistical Methods

مجلة بغداد للعلوم, 2020
An image retrieval system is a computer system for browsing, looking and recovering pictures from a huge database of advanced pictures. The objective of Content-Based Image Retrieval (CBIR) methods is essentially to extract, from large (image) databases,
Fathala Ali et al.
doaj   +3 more sources

AI powered multi feature fusion framework for retrieving images using color, texture and shape descriptors [PDF]

Scientific Reports
The exponential expansion of digital visual material requires sophisticated and efficient picture retrieval technologies. The article presents a new framework using AI to integrate form descriptors, texture patterns, and color histograms to improve ...
Kommu Naveen, R. M. S. Parvathi
doaj   +2 more sources

Entropy guided multi level feature fusion network for high precision content based image retrieval [PDF]

Scientific Reports
Content-based image retrieval (CBIR) is essential for managing and searching massive image repositories across a wide variety of applications. Nevertheless, some traditional CBIR systems exhibit low retrieval accuracy because they use predetermined ...
M. Lavanya, G. Vennira Selvi, R. Gopi, A. C. Vimal Raj   +3 more
doaj   +2 more sources

Convolutional Fine-Tuned Threshold Adaboost approach for effectual content-based image retrieval [PDF]

Scientific Reports
Applications for content-based image retrieval (CBIR) are found in a wide range of industries, including e-commerce, multimedia, and healthcare. CBIR is essential for organising and obtaining visual data from massive databases.
Robert Cep, Muniyandy Elangovan, Janjhyam Venkata Naga Ramesh, Mandeep Kaur Chohan, Amit Verma   +4 more
doaj   +2 more sources

Evaluation of a content-based image retrieval system for radiologists in high-resolution CT of interstitial lung diseases [PDF]

European Radiology Experimental
Background This retrospective study aims to evaluate the impact of a content-based image retrieval (CBIR) application on diagnostic accuracy and confidence in interstitial lung disease (ILD) assessment using high-resolution computed tomography CT (HRCT).
Benjamin Böttcher, Marly van Assen, Roberto Fari, Philipp L. von Knebel Doeberitz, Eun Young Kim, Eugene A. Berkowitz, Felix G. Meinel, Carlo N. De Cecco   +7 more
doaj   +2 more sources

Content-Based Image Retrieval and Image Classification System for Early Prediction of Bladder Cancer [PDF]

Diagnostics
Background/Objectives: Bladder cancer is a type of cancer that begins in the cells lining the inner surface of the bladder. Although it usually begins in the bladder, it can spread to surrounding tissues, lymph nodes, and other organs in later stages ...
Muhammed Yildirim
doaj   +2 more sources

An approach for improving the performance of the Content-Based Image Retrieval (CBIR)

Journal of the Korean Society of Surveying Geodesy Photogrammetry and Cartography, 2012
Amid rapidly increasing imagery inputs and their volume in a remote sensing imagery database, Content-Based Image Retrieval (CBIR) is an effective tool to search for an image feature or image content of interest a user wants to retrieve. It seeks to capture salient features from a 'query' image, and then to locate other instances of image region having
exaly   +3 more sources

Cross-modality sub-image retrieval using contrastive multimodal image representations [PDF]

Scientific Reports
In tissue characterization and cancer diagnostics, multimodal imaging has emerged as a powerful technique. Thanks to computational advances, large datasets can be exploited to discover patterns in pathologies and improve diagnosis. However, this requires
Eva Breznik, Elisabeth Wetzer, Joakim Lindblad, Nataša Sladoje   +3 more
doaj   +2 more sources

CBIR-ANR: A content-based image retrieval with accuracy noise reduction

Software Impacts, 2023
Gabriel S Vieira, Afonso U Fonseca, Fabrizzio Soares   +2 more
exaly   +2 more sources