Dual Modality Reverse Reranking (DM-RR) Based Image Retrieval Framework Article Swipe
Ikhlaq Ahmed
,
Naima Iltaf
,
Rabia Latif
,
Nor Shahida Mohd Jamail
,
Zafran Khan
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1109/ojies.2024.3435956
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1109/ojies.2024.3435956
Retrieval of a product with desired modifications from a vast inventory of online industrial platforms is frequently encountered in our daily life. This study presents a specialized framework to retrieve user's queried product with its desired changes incorporated. To facilitate interaction between the end-user and agent in such scenarios, a multimodal content-based image retrieval system is essential. The system extracts textual and visual attributes, combining them through inductive learning to a unified representation. It is based on an in-depth understanding of visual characteristics that are modified by textual semantics. Lastly, a novel reverse reranking (RR) algorithm arranges the joint representation of dual modality queries and their corresponding target images for efficient retrieval. The proposed framework is novel compared to earlier methodologies. First, it achieves successful fusion of two different modalities. Second, it introduces a RR algorithm in the inference stage for efficient retrieval. The proposed framework's enhanced performance has been assessed using the Fashion-200 K and MIT-States real-world benchmark datasets. The proposed system can be used in real-world applications subject to its practical implications, such as generalization to diverse domains, availability of domain specific data, nature of the data and queries, and availability of computational resources.
Related Topics
Concepts
Computer science
Ranking (information retrieval)
Information retrieval
Modality (human–computer interaction)
Benchmark (surveying)
Image retrieval
Semantics (computer science)
Domain (mathematical analysis)
Representation (politics)
Artificial intelligence
Modalities
Data mining
Machine learning
Image (mathematics)
Programming language
Sociology
Social science
Political science
Mathematical analysis
Politics
Geography
Mathematics
Geodesy
Law
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/ojies.2024.3435956
- OA Status
- gold
- Cited By
- 1
- References
- 44
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4401113437
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4401113437Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/ojies.2024.3435956Digital Object Identifier
- Title
-
Dual Modality Reverse Reranking (DM-RR) Based Image Retrieval FrameworkWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-01-01Full publication date if available
- Authors
-
Ikhlaq Ahmed, Naima Iltaf, Rabia Latif, Nor Shahida Mohd Jamail, Zafran KhanList of authors in order
- Landing page
-
https://doi.org/10.1109/ojies.2024.3435956Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1109/ojies.2024.3435956Direct OA link when available
- Concepts
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Computer science, Ranking (information retrieval), Information retrieval, Modality (human–computer interaction), Benchmark (surveying), Image retrieval, Semantics (computer science), Domain (mathematical analysis), Representation (politics), Artificial intelligence, Modalities, Data mining, Machine learning, Image (mathematics), Programming language, Sociology, Social science, Political science, Mathematical analysis, Politics, Geography, Mathematics, Geodesy, LawTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
- References (count)
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44Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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