Results 51 to 60 of about 36,977,793 (187)

Leveraging foundation models for content-based image retrieval in radiology [PDF]

Comput. Biol. Medicine
Content-based image retrieval (CBIR) has the potential to significantly improve diagnostic aid and medical research in radiology. However, current CBIR systems face limitations due to their specialization to certain pathologies, limiting their utility ...
Stefan Denner, D. Zimmerer, D. Bounias, Markus Bujotzek, Shu-Han Xiao, Raphael Stock, Lisa Kausch, P. Schader, T. Penzkofer, P. Jäger, Klaus H. Maier-Hein   +10 more
semanticscholar   +1 more source

A Domain‐Specific Vision Foundation Model for Mars: Self‐Supervised Learning for Planetary‐Scale Science Discovery

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Planetary missions have produced a rapidly growing archive of high‐resolution imagery, yet only a small fraction has been examined in detail. Foundation models (FMs) offer a scalable path by learning transferable representations from unlabeled data, but most vision backbones are trained on Internet imagery or Earth observation data sets that ...
J. Fang, W. Luo, Q. Huang, L. Zhang, M. S. Phillips, V. D. R. Seethi, I. Giannakis   +6 more
wiley   +1 more source

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  

Implementation of Content-Based Image Retrieval Using Artificial Neural Networks

Engineering Proceedings, 2023
CBIR (Content Based Image Retrieval) has become a critical domain in the previous decade, owing to the rising demand for image retrieval from multimedia databases.
Sarath Chandra Yenigalla, Karumuri Srinivasa Rao, Phalguni Singh Ngangbam   +2 more
doaj   +1 more source

Brain‐RetinaNet: Detection of Brain Tumour Using an Improved RetinaNet in Magnetic Resonance Imaging

CAAI Transactions on Intelligence Technology, Volume 11, Issue 1, Page 223-237, February 2026.
ABSTRACT Brain tumours disrupt the normal functioning of the brain and, if left untreated, can invade surrounding tissues, blood vessels, and nerves, posing a severe threat. Consequently, early detection is crucial to prevent tragic outcomes. Distinguishing brain tumours through manual detection poses a significant challenge given their diverse ...
Rashid Iqbal, Rabbia Mahum, Mohamed Sharaf, Javed Ali Khan   +3 more
wiley   +1 more source

A secure encrypted CBIR and explainable hybrid deep learning framework for clothing recommendation

Discover Applied Sciences
The traditional CBIR systems that are heavily dependent on low, level features of the image for information retrieval have been criticized for low accuracy and low transparency. As per the latest requirements, such systems need to be equipped with models
Akanksha Mrinali, Pankaj Gupta, Yeswanth Dintakurthy, Arun Kumar Soma, K. R. K. V. Prasad, Jawad Khan, Mohammed Wasim Bhatt   +6 more
doaj   +1 more source

Hidden Tumour Visualization in Augmented Monocular Liver Laparoscopy

Healthcare Technology Letters, Volume 13, Issue 1, January/December 2026.
We have proposed a novel visualization method with three visualization variants for hidden tumours in liver laparoscopy. We propose a visualization that convinces users to see the tumour inside the organ and provides metric depth perception. ABSTRACT We address the hidden tumour visualization problem in augmented monocular liver laparoscopy.
Kirana Hanifati, Mohammad Alkhatib, Erol Ozgur, Emmanuel Buc, Bertrand Le Roy, Hestiasari Rante, Youcef Mezouar, Adrien Bartoli   +7 more
wiley   +1 more source

Self-feedback image retrieval algorithm based on annular color moments

EURASIP Journal on Image and Video Processing, 2019
Content-based image retrieval (CBIR) extracts visual content features (such as color, texture, and shape) of a sample image to retrieve another similar image. Due to the existence of the semantic gap, retrieval results are often unsatisfactory.
Ying Deng, Yuanhui Yu
doaj   +1 more source

Deep image retrieval using artificial neural network interpolation and indexing based on similarity measurement

CAAI Transactions on Intelligence Technology, 2022
In content‐based image retrieval (CBIR), primitive image signatures are critical because they represent the visual characteristics. Image signatures, which are algorithmically descriptive and accurately recognized visual components, are used to ...
Faiyaz Ahmad
doaj   +1 more source

A Large‐Scale Dataset and Robust Multifeature Representation With Maximum Correlation‐Based Feature Fusion and Matching for Apparel Image Retrieval

Expert Systems, Volume 42, Issue 9, September 2025.
ABSTRACT Finding the correct match to a probe image from a vast amount of data is critical for the online retrieval of apparel images. These images are captured under an uncontrolled environment (e.g., viewpoint and illumination changes); therefore, such type of data is extremely challenging in Content‐Based Image Retrieval (CBIR) research.
Marryam Murtaza, Muhammad Fayyaz, Mussarat Yasmin, Muhammad Anwar, Kashif Naseer Qureshi, Usman Ahmed Raza   +5 more
wiley   +1 more source