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Image Retrieval and Classification Techniques

TopicLeading institutions, researchers & key papers

Image Retrieval and Classification Techniques is a topic indexed in ScholarIQ from OpenAlex.

What is known about Image Retrieval and Classification Techniques?

ScholarIQrecord summary

This cluster of papers focuses on shape matching, object recognition, and content-based image retrieval using techniques such as local binary patterns, feature descriptors, and rotation-invariant methods. It also explores the application of these methods in medical imaging, semantic relevance modeling, and machine learning for image annotation.

How many works does Image Retrieval and Classification Techniques have?

ScholarIQindexed works

Image Retrieval and Classification Techniques has 166 works in the ScholarIQ index. The count is the OpenAlex total, not the number of papers listed on this page.

What is the OpenAlex record for Image Retrieval and Classification Techniques?

ScholarIQopenalex

The OpenAlex for Image Retrieval and Classification Techniques is on the source record.

What are the most-cited papers on Image Retrieval and Classification Techniques?

ScholarIQmost cited works
ShapeNet: An Information-Rich 3D Model Repository
Chang, Angel X., Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Yi Li, Fisher Yu
arXiv (Cornell University). 20152,381 CitationsOPEN ACCESS
A New Local Adaptive Thresholding Technique in Binarization
Tripty Singh, Sudipta Roy, O. Imocha Singh, Tejmani Sinam, Kh. Manglem Singh
arXiv (Cornell University). 2012228 CitationsOPEN ACCESS
A large-scale hierarchical image database
Jie Deng
Medical Entomology and Zoology. 2009198 Citations
Multiscale Medial Loci and Their Properties
Stephen M. Pizer, Kaleem Siddiqi, Gábor Székely, James Damon, Steven W. Zucker
International Journal of Computer Vision. 2003176 Citations

Where is Image Retrieval and Classification Techniques research published, and who funds it?

ScholarIQvenues & funding sources

TOP FUNDERS

National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
Funder breakdown is a member featureSign up free to unlock

How much of the research on Image Retrieval and Classification Techniques is open access?

ScholarIQopen access share
33%OPEN ACCESS
Gold
7%
Green
27%
Hybrid
0%
Bronze
0%
Closed
67%

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