Results 181 to 190 of about 2,978 (220)

An open-source, automated machine learning approach for large-scale image retrieval for thoracic aorta analysis studies. [PDF]

JAMIA Open
Ayers BC, Aguirre AD, Sundt TM, Lu MT, Jassar A.   +4 more
europepmc   +1 more source

DFF-CBIR: Deep Feature Fusion Framework for Enhanced Content-Based Image Retrieval

IEEE Access
Surbhi Tyagi, Praveen Kumar Shukla, Partap Singh   +2 more
openaire   +1 more source

Unsupervised Content Mining in CBIR: Harnessing Latent Diffusion for Complex Text-Based Query Interpretation. [PDF]

J Imaging
Gopu VRMK, Dunna M.
europepmc   +1 more source

Towards Interactive and Interpretable Image Retrieval-Based Diagnosis: Enhancing Brain Tumor Classification with LLM Explanations and Latent Structure Preservation. [PDF]

Artif Intell Med Conf Artif Intell Med (2005-)
Manjunath P, Lerner B, Dunn T.
europepmc   +1 more source

Content-based image retrieval of Indian traditional textile motifs using deep feature fusion. [PDF]

Sci Rep
Varshney S, Singh S, Lakshmi CV, Patvardhan C.   +3 more
europepmc   +1 more source

Mutual contextual relation-guided dynamic graph networks for cross-modal image-text retrieval. [PDF]

Sci Rep
Sucharitha G, Kalyani BJD, Raju ASN, Sitharamulu V, Guntreddi V, Potluri S.   +5 more
europepmc   +1 more source

Structured hashing with deep learning for modality, organ, and disease content sensitive medical image retrieval. [PDF]

Sci Rep
Manna A, Dewan D, Sheet D.
europepmc   +1 more source

Efficient Image Retrieval Using Hierarchical K-Means Clustering. [PDF]

Sensors (Basel)
Park D, Hwang Y.
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Evaluation of retrieval accuracy and visual similarity in content-based image retrieval of chest CT for obstructive lung disease. [PDF]

Sci Rep
Choe J, Choi HY, Lee SM, Oh SY, Hwang HJ, Kim N, Yun J, Lee JS, Oh YM, Yu D, Kim B, Seo JB.   +11 more
europepmc   +1 more source

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Content-based image retrieval from videos using CBIR and ABIR algorithm

2015 Global Conference on Communication Technologies (GCCT), 2015
Content-based video retrieval is very interesting point where it can be used in our daily life. Video retrieval is regarded as one of the most important in multimedia research. The development of multimedia data types there is demand of video retrieval system.
Vrushali A. Wankhede, Prakash S. Mohod
exaly   +2 more sources