Results 11 to 20 of about 230,040 (300)
Explainable, interactive content‐based image retrieval
Quantifying the value of explanations in a human‐in‐the‐loop (HITL) system is difficult. Previous methods either measure explanation‐specific values that do not correspond to user tasks and needs or poll users on how useful they find the explanations to ...
Bhavan Vasu +4 more
doaj +1 more source
In the era of massive data production through the internet and social media, the volume of images generated is immense. Storing and retrieving relevant images efficiently pose significant challenges.
Divya Srivastava +5 more
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Content‐based image retrieval (CBIR) is the problem of searching for items in an image database that are similar to the query image. Most of the existing image retrieval methods are trained based on metric learning loss functions (e.g.
Jinliang Yao +3 more
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Content-Based Medical Image Retrieval with Opponent Class Adaptive Margin Loss [PDF]
Broadspread use of medical imaging devices with digital storage has paved the way for curation of substantial data repositories. Fast access to image samples with similar appearance to suspected cases can help establish a consulting system for healthcare
Ş. Öztürk, Emin Çelik, Tolga Cukur
semanticscholar +1 more source
SPECTRAL ALGORITHM FOR CONTENT-BASED IMAGE RETRIEVAL
Colour images are rich in visual information. The process of searching for the most similar images in large-scale database based on visual features of query image is still a challenge in Content-Based Image Retrieval (CBIR) due to a semantic gap issue ...
Hanan A. Al-Jubouri, Sawsan M. Mahmmod
doaj +3 more sources
Correlated Networks for Content Based Image Retrieval [PDF]
Efficient CBIR systems are based on three things, (1) how they represent the repository images in the form of signature; (2) how they measure the similarity of the database images with query image, (3) how they retrieve the semantically similar images in
Aun Irtaza, M. Arfan Jaffar, Eisa Aleisa
doaj +1 more source
With the passing years, many advanced technologies have come into existence for efficientimage retrieval. Research in content-based image retrieval (CBIR) in the past has been focused on image processing, low-level feature extraction. The accuracy of retrieval has subsequently increased with the use of low level features such as color, texture, shape ...
HARSHADA ANAND KHUTWAD +1 more
openaire +2 more sources
Encrypted Image Retrieval System based on Features Analysis
– Content-based search provides an important tool for users to consume the ever-growing digital media repositories. However, since communication between digital products takes place in a public network, the necessity of security for digital images ...
Methaq Talib GAATA, Fadya Fouad Hantoosh
doaj +1 more source
Medical Image Retrieval: Past and Present [PDF]
With the widespread dissemination of picture archiving and communication systems (PACSs) in hospitals, the amount of imaging data is rapidly increasing. Effective image retrieval systems are required to manage these complex and large image databases. The
Kyung Hoon Hwang +2 more
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Content-based medical image retrieval system for lung diseases using deep CNNs
Content-based image retrieval (CBIR) systems are designed to retrieve images that are relevant, based on detailed analysis of latent image characteristics, thus eliminating the dependency of natural language tags, text descriptions, or keywords ...
Shubham Agrawal +4 more
semanticscholar +1 more source

