Results 61 to 70 of about 2,978 (220)

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

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

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

Content-based Image Retrieval (CBIR) using Hybrid Technique

International Journal of Computer Applications, 2013
retrieval is used in searching for images from images database. In this paper, content - based image retrieval (CBIR) using four feature extraction techniques has been achieved. The four techniques are colored histogram features technique, properties features technique, gray level co- occurrence matrix (GLCM) statistical features technique and hybrid ...
Nabeel Jameel Tawfiq, Israa Jameel Muhsin, Zainab IbrahimAbood   +2 more
openaire   +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

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

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

Content Based Image Retrieval Using Embedded Neural Networks with Bandletized Regions

Entropy, 2015
One of the major requirements of content based image retrieval (CBIR) systems is to ensure meaningful image retrieval against query images. The performance of these systems is severely degraded by the inclusion of image content which does not contain the
Rehan Ashraf, Khalid Bashir, Aun Irtaza, Muhammad Tariq Mahmood   +3 more
doaj   +1 more source

Multiple layar kernel-based approach in relevance feedback content-based image retrieval system

, 2005
Relevance feedback has drawn intense interest from many researchers in the field of content-based image retrieval (CBIR). In recent years, kernel-based approach has been a popular choice for the implementation of the relevance feedback based CBIR system.
Chun-Che Fung, Fung, C.C., Chung, K.P., Kien-Ping Chung   +3 more
core   +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