Results 71 to 80 of about 2,978 (220)

The Content-Driven Preprocessor of Images for MPEG-7 Descriptions [PDF]

Journal of Systemics, Cybernetics and Informatics, 2003
An image content-driven (CDP) preprocessor is proposed to activate the right MPEG-7 description tools for the recognized feature contents in one image.
Jiann-Jone Chen, Cheng-Yi Liu, Feng-Cheng Chang   +2 more
doaj  

A Study on the Channel Expansion VAE for Content-Based Image Retrieval

Applied Sciences, 2022
Content-based image retrieval (CBIR) focuses on video searching with fine-tuning of pre-trained off-the-shelf features. CBIR is an intuitive method for image retrieval, although it still requires labeled datasets for fine-tuning due to the inefficiency ...
Kyounghak Lee, Yeonghun Lee, Hyung-Hwa Ko, Minsoo Kang   +3 more
doaj   +1 more source

A Systematic Mapping Study of the Metrics, Uses and Subjects of Diversity‐Based Testing Techniques

Software Testing, Verification and Reliability, Volume 35, Issue 2, March 2025.
This paper is a systematic mapping study of diversity‐based testing (DBT) techniques that summarizes the key aspects and trends of 167 papers. The study reports the use of 79 similarity metrics with 22 types of software artefacts, which researchers have used to tackle 11 types of software testing problems.
Islam T. Elgendy, Robert M. Hierons, Phil McMinn   +2 more
wiley   +1 more source

Adaptive Two‐Tier Deep Learning for Content‐Based Image Retrieval and Classification With Dynamic Similarity Fusion

IET Image Processing, Volume 19, Issue 1, January/December 2025.
We present a two‐tier deep learning framework for content‐based image retrieval, combining pixel‐level colour classification with image‐level classification and adaptive feature fusion. The system dynamically optimises structural and semantic similarity weights (alpha and beta) via neural prediction, achieving 0.87 0.99 precision across medical and ...
Aqeel M. Humadi, Mehdi Sadeghzadeh, Hameed A. Younis, Mahdi Mosleh   +3 more
wiley   +1 more source

A novel content-based image retrieval system using custom CNN and data augmentation for improved rotation robustness

AIP Advances
Content-Based Image Retrieval (CBIR) is essential for retrieving images through visual content comparison, addressing the limitations of traditional keyword-based searches.
Monica Palla, Renu Karra
doaj   +1 more source

Hybrid Model for Visual Sentiment Classification Using Content‐Based Image Retrieval and Multi‐Input Convolutional Neural Network

International Journal of Intelligent Systems, Volume 2025, Issue 1, 2025.
With the exponential growth of multimedia content, visual sentiment classification has emerged as a significant research area. However, it poses unique challenges due to the complexity and subjective nature of the visual information. This can be attributed to the significant presence of semantically ambiguous images within the current benchmark ...
Israa K. Salman Al-Tameemi, Mohammad-Reza Feizi-Derakhshi, Zari Farhadi, Amir-Reza Feizi-Derakhshi, Yingjie Yang   +4 more
wiley   +1 more source

Content-Based Image Retrieval (CBIR) in Big Histological Image Databases

Medical Technologies Journal, 2020
Background: Automatic analysis of Histopathological Images (HIs) demands image processing and Computational Intelligence (CI) techniques. Both Computer-Aided Diagnosis (CAD) and Content-Based Image-Retrieval (CBIR) systems assist diagnosis, disease discovery, and biological decision-making.
openaire   +2 more sources

Video information retrieval using objects and ostensive relevance feedback [PDF]

, 2004
In this paper, we present a brief overview of current approaches to video information retrieval (IR) and we highlight its limitations and drawbacks in terms of satisfying user needs.
Browne, Paul
core   +1 more source

Multifeature Fusion for Enhanced Content‐Based Image Retrieval Across Diverse Data Types

Journal of Electrical and Computer Engineering, Volume 2025, Issue 1, 2025.
There is a growing trend for using content‐based image retrieval (CBIR) systems these days because of the constantly growing interest in digital content. Therefore, the ability of the CBIR to perform the CBIR process will depend on the feature extraction process and its basis, for the retrieval will be done on.
Punit Soni, Mandeep Singh, Purushottam Sharma, Tajinder Kumar, Xiaochun Cheng, Rajender Kumar, Mrinal Paliwal, Kanwarpreet Kaur   +7 more
wiley   +1 more source

SkinSage XAI: An explainable deep learning solution for skin lesion diagnosis

Health Care Science, Volume 3, Issue 6, Page 438-455, December 2024.
The research was meant to disentangle the difficulties of skin lesion diagnosis using a multimodal approach. Our suggested technique offers unparalleled levels of transparency and interpretability in skin lesion categorization and marks a substantial improvement in the area via methodical methodology and meticulous refining.
Geetika Munjal, Paarth Bhardwaj, Vaibhav Bhargava, Shivendra Singh, Nimish Nagpal   +4 more
wiley   +1 more source