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Multimodal concept-dependent active learning for image retrieval
2004
Proceedings of the 12th annual ACM international conference on Multimedia - MULTIMEDIA '04
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It has been established that active learning is effective for learning complex, subjective query concepts for image retrieval. ...
We then propose a multimodal learning approach that uses images' semantic labels to guide a concept-dependent, active-learning process. ...
CONCLUSIONS We have proposed a multimodal, concept-dependent active learning scheme CDAL, which combines keywords with images' perceptual features in a synergistic way to perform image retrieval. ...
doi:10.1145/1027527.1027664
dblp:conf/mm/GohCL04
fatcat:yq5qccle7vf7dnkiz65j2ttx7a
Early_and_Late_Fusion_of_Multiple_Modalities_in_Sentinel_Image_Retrieval
2020
Zenodo
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In the early fusion part, the model is based on active learning that effectively merges Sentinel-1 and Sentinel-2 bands, and assists users to extract patterns. ...
On the other hand, the late fusion mechanism exploits the context of other geo-referenced data such as social media retrieval, to further enrich the list of retrieved Sentinel image patches. ...
Our contribution is summarized as follows: -Retrieve satellite images using an active learning technique -Extend satellite image retrieval with social media posts The paper is organised as follows. ...
doi:10.5281/zenodo.4280738
fatcat:qv7nqqqumrbifodqt5jrgvkhva
A Survey on Visual Search Reranking
2014
IOSR Journal of Computer Engineering
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However the problem is not trivial especially when we are considering multiple features or modalities for search in image and video retrieval. ...
Search reranking is considered as a best and common way to improves retrieval precision. ...
Kennedy et al, [9] , proposed a query class dependent search models in multimodal retrieval for the automatic discovery of query classes. ...
doi:10.9790/0661-16197881
fatcat:7txgqtlicnfcffteakolplwdji
Image Retrieval and Re-Ranking Techniques - A Survey
2014
Signal & Image Processing An International Journal
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The technique leaves no ambiguities as we consider only the variant characteristics or modalities, in order to gain the image and video retrieval. ...
To improve retrieval precision, no other technique is as useful the re-ranking technique. ...
Kennedy et al, [9] , proposed a query class dependent search models in multimodal retrieval for the automatic discovery of query classes. ...
doi:10.5121/sipij.2014.5201
fatcat:gusz6wizpbgsfgjt6asf7s44fi
Overview on Image Captioning Techniques
2021
International Journal of Emerging Trends in Engineering Research
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Key words : Computer Vision, Deep Learning, Neural Network, NLP, Image Captioning, Multimodal Learning. ...
Captioning of an image first need to identify object, attribute and relationship among these in image and second is to generate relevant description for the given image. ...
This method depends on high level image feature and representation of word learned from multimodal neural language modal and deep neural network. "A Karpathy et al. ...
doi:10.30534/ijeter/2021/15982021
fatcat:kt2h543eg5fctggmxghc352siu
Self-Supervised Learning from Web Data for Multimodal Retrieval
[article]
2019
arXiv
pre-print
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model for semantic image retrieval. ...
Self-Supervised learning from multimodal image and text data allows deep neural networks to learn powerful features with no need of human annotated data. ...
program from the Generalitat de Catalunya, the Spanish project TIN2017-89779-P, the H2020 Marie Skłodowska-Curie actions of the European Union, grant agreement No 712949 (TECNIOspring PLUS), and the Agency for ...
arXiv:1901.02004v1
fatcat:wpibqwyf2rax7ltrahjnw6vvxy
A Survey on Multimodal Video Representation for Semantic Retrieval
2005
EUROCON 2005 - The International Conference on "Computer as a Tool"
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This paper surveys the approaches to video representation, focusing on semantic analysis for content-based indexing and retrieval. ...
Furthermore, the concept of video multimodality is reevaluated and redefined in order to introduce modalities such as editing technique or affect to the audience. ...
ACKNOWLEDGEMENTS The work reported in this paper has formed part of the activity of the WG3 within IST COST292 action in semantic multimodal analysis of digital media whose funding and support is gratefully ...
doi:10.1109/eurcon.2005.1629877
fatcat:e25kjkfqx5fplht6rrnavhwy54
Probing Contextualized Sentence Representations with Visual Awareness
[article]
2019
arXiv
pre-print
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For each sentence, we first retrieve a diversity of images from a shared cross-modal embedding space, which is pre-trained on a large-scale of text-image pairs. ...
The architecture can be easily applied to text-only natural language processing tasks without manually annotating multimodal parallel corpora. ...
Figure 3 : 3 Examples of the retrieved images for sentences.
Figure 4 : 4 Concept activation maps with different input words. The orange region indicates the highest peak in the heatmap. ...
arXiv:1911.02971v1
fatcat:xeisuobbzbb5pkymubliv2kf4q
Learning to Learn from Web Data through Deep Semantic Embeddings
[article]
2018
arXiv
pre-print
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for semantic image retrieval. ...
Further we demonstrate how semantic multimodal image retrieval can be performed using the learnt embeddings, going beyond classical instance-level retrieval problems. ...
program from the Generalitat de Catalunya, the Spanish project TIN2017-89779-P, the H2020 Marie Skłodowska-Curie actions of the European Union, grant agreement No 712949 (TECNIOspring PLUS), and the Agency for ...
arXiv:1808.06368v1
fatcat:m4dtjcxevnfmdgz7z47rzulv3e
Learning to Learn from Web Data Through Deep Semantic Embeddings
[chapter]
2019
Lecture Notes in Computer Science
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for semantic image retrieval. ...
Further we demonstrate how semantic multimodal image retrieval can be performed using the learnt embeddings, going beyond classical instance-level retrieval problems. ...
program from the Generalitat de Catalunya, the Spanish project TIN2017-89779-P, the H2020 Marie Skłodowska-Curie actions of the European Union, grant agreement No 712949 (TECNIOspring PLUS), and the Agency for ...
doi:10.1007/978-3-030-11024-6_40
fatcat:crzepesrz5bglj3bmunkldk6ey
Supervised models for multimodal image retrieval based on visual, semantic and geographic information
2012
2012 10th International Workshop on Content-Based Multimedia Indexing (CBMI)
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Multimodal approaches are promising technologies to improve image ranking. ...
More specifically, we combine visual features, which strongly relate to the image content, with semantic information represented by manually annotated concepts, and geo tagging, very often available in ...
Figures 2 and 3 show the results for k retrieved images for each query, where the k values are listed on the x-axis. ...
doi:10.1109/cbmi.2012.6269806
dblp:conf/cbmi/Dang-NguyenBMN12
fatcat:f4tafe2m6jc2hi7rmsvx33vxmi
Image pseudo tag generation with Deep Boltzmann machine anc topic-concept similarity map
2017
2017 International Joint Conference on Neural Networks (IJCNN)
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for efficient learning on image features. ...
Unsupervised Pseudo Tag Generation The above approach for pseudo tag generation is dependent on the supervised concept classification results in the image modality. ...
doi:10.1109/ijcnn.2017.7966003
dblp:conf/ijcnn/IshikawaLK17
fatcat:bbaio5lcnvewxorpwzuozkaxee
Layered Hypernetwork Models for Cross-Modal Associative Text and Image Keyword Generation in Multimodal Information Retrieval
[chapter]
2010
Lecture Notes in Computer Science
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Conventional methods for multimodal data retrieval use text-tag based or cross-modal approaches such as tag-image co-occurrence and canonical correlation analysis. ...
Here, we propose a novel text and image keyword generation method by cross-modal associative learning and inference with multimodal queries. ...
Goh et al. proposed an image retrieval method based on multimodal concept-dependent active learning [2] . ...
doi:10.1007/978-3-642-15246-7_10
fatcat:yvileqmhfnf6jhmvjwfuzzgmsm
DeepStyle: Multimodal Search Engine for Fashion and Interior Design
2019
IEEE Access
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INDEX TERMS Multimedia computing, multi-layer neural network, multimodal search, machine learning. ...
Existing search engines treat textual input only as an additional source of information about the query image and do not correspond to the real-life scenario, where the user looks for "the same shirt but ...
Another recent VQA approach for multimodal representation learning from text and image is MUTAN [30] . ...
doi:10.1109/access.2019.2923552
fatcat:4qjj4f52rrav5mjuqgyd7ictzm
Content-based indexing of multimedia databases
1997
IEEE Transactions on Knowledge and Data Engineering
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Content-based retrieval of multimedia database calls for content-based indexing techniques. ...
These lead to great challenges for content-based indexing. ...
As far as retrieval accuracy concerned, it is sole dependent on the feature measures extracted, and similarity function used in the retrieval. ...
doi:10.1109/69.649320
fatcat:u5bsvkwzqrdzbmqvm7ybvedvpi
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