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Visual Query Expansion via Incremental Hypernetwork Models of Image and Text [chapter]

Min-Oh Heo, Myunggu Kang, Byoung-Tak Zhang
2010 Lecture Notes in Computer Science  
Here, we propose a visual query expansion method that simulates the capability of human associative memory. We use a hyperenetwork model (HN) that combines visual words and linguistic words.  ...  An incremental HN generates images by assembling visual words based on linguistic cues. And we retrieve similar images with the generated visual query.  ...  For the visual query expansion, it is mainly used to improve the performance of the retrieval task. Chum et al. introduced query expansion using images by analogy for the text retrieval.  ... 
doi:10.1007/978-3-642-15246-7_11 fatcat:3dlagta7ijd3tkrhu7yuyszdrm

Text-to-image retrieval based on incremental association via multimodal hypernetworks

Jung-Woo Ha, Beom-Jin Lee, Byoung-Tak Zhang
2012 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)  
Using the HN incrementally learned by a sequential Bayesian sampling, in the multimodal hypernetwork-based text-to-image retrieval, a given text query is crossmodally expanded to the visual query and then  ...  Here we propose an incremental text-to-image retrieval method using a multimodal association model.  ...  Moreover, the images related to the text queries are retrieved by crossmodal query expansion with the learned model.  ... 
doi:10.1109/icsmc.2012.6378291 dblp:conf/smc/HaLZ12 fatcat:a6bxtihwnncarfinib6e3hgpne

Opportunities and obstacles for deep learning in biology and medicine

Travers Ching, Daniel S. Himmelstein, Brett K. Beaulieu-Jones, Alexandr A. Kalinin, Brian T. Do, Gregory P. Way, Enrico Ferrero, Paul-Michael Agapow, Michael Zietz, Michael M. Hoffman, Wei Xie, Gail L. Rosen (+24 others)
2018 Journal of the Royal Society Interface  
We examine applications of deep learning to a variety of biomedical problems-patient classification, fundamental biological processes and treatment of patients-and discuss whether deep learning will be  ...  Nonetheless, we foresee deep learning enabling changes at both bench and bedside with the potential to transform several areas of biology and medicine.  ...  We thank Aaron Sheldon, who contributed text but did not formally approve the manuscript; Anna Greene for a careful proofreading of the manuscript in advance of the first submission; Sebastian Raschka  ... 
doi:10.1098/rsif.2017.0387 pmid:29618526 pmcid:PMC5938574 fatcat:65o4xmp53nc6zmj37srzuht6tq

Knowledge Graphs [article]

Aidan Hogan, Eva Blomqvist, Michael Cochez, Claudia d'Amato, Gerard de Melo, Claudio Gutierrez, José Emilio Labra Gayo, Sabrina Kirrane, Sebastian Neumaier, Axel Polleres, Roberto Navigli, Axel-Cyrille Ngonga Ngomo (+6 others)
2021 arXiv   pre-print
After some opening remarks, we motivate and contrast various graph-based data models and query languages that are used for knowledge graphs.  ...  We discuss the roles of schema, identity, and context in knowledge graphs. We explain how knowledge can be represented and extracted using a combination of deductive and inductive techniques.  ...  Acknowledgements: We thank the attendees of the Dagstuhl Seminar on "Knowledge Graphs" for discussions that inspired and influenced this paper, and all those that make such seminars possible.  ... 
arXiv:2003.02320v5 fatcat:ab4hmm2f2bbpvobwkjw4xbrz4u

Automated Deep Learning: Neural Architecture Search Is Not the End [article]

Xuanyi Dong, David Jacob Kedziora, Katarzyna Musial, Bogdan Gabrys
2022 arXiv   pre-print
Deep learning (DL) has proven to be a highly effective approach for developing models in diverse contexts, including visual perception, speech recognition, and machine translation.  ...  It requires grappling with problem formulation and context understanding, data engineering, model development, deployment, continuous monitoring and maintenance, and so on.  ...  Acknowledgments: XD and DJK acknowledge financial support secured by BG, which funded their participation in this study and the ongoing "Automated and Autonomous Machine Learning" project as part of the  ... 
arXiv:2112.09245v3 fatcat:dujfh7pzmzbrtdyoshkl4kpbsm

D1.1 - State of the Art Analysis

Danilo Ardagna
2021 Zenodo  
In the last part of the deliverable, we report an overview of the performance modelling solutions, security, and privacy problems for AI applications in edge environments.  ...  The aim of this deliverable is to review the state-of-the-art in techniques used in the development and operation of AI applications in computing continua and the related technologies.  ...  Language Classifier, Visual tool and API for text classification • IBM Watson Speech-to-Text and Text-to-Speech • IBM Watson Machine Learning, Infrastructure for running AI models at scale • IBM Streaming  ... 
doi:10.5281/zenodo.6372377 fatcat:f6ldfuwivbcltew4smiiwphfty

Graph Neural Networks: Taxonomy, Advances and Trends [article]

Yu Zhou, Haixia Zheng, Xin Huang, Shufeng Hao, Dengao Li, Jumin Zhao
2022 arXiv   pre-print
First of all, we provide a novel taxonomy for the graph neural networks, and then refer to up to 400 relevant literatures to show the panorama of the graph neural networks.  ...  It is expected that more and more scholars can understand and exploit the graph neural networks, and use them in their research community.  ...  Acknowledgements This work was supported by National Natural Science Foundation of China (Grant No. 62002255).  ... 
arXiv:2012.08752v3 fatcat:xj2kambrabfj3g5ldenfyixzu4

Dynamic Mathematics for Automated Machine Learning Techniques [article]

Nicholas Kuo, University, The Australian National
Machine learning is not simple; it requires a practitioner to have thorough understanding on the attributes of their data and the components which their model entails.  ...  Machine Learning and Neural Networks have been gaining popularity and are widely considered as the driving force of the Fourth Industrial Revolution.  ...  One of the most common applications of RNNs is the NLP of text for language modelling.  ... 
doi:10.25911/zmy2-7160 fatcat:flnkwfv33rbupg2e5m4twnbaie

Cities in interaction

Antoine Peris
Using text as data appeared as a great direction for studying urban systems, and elements from this first exploration are used in the next section of the thesis where the past dynamics of the Dutch urban  ...  This method aims at identifying patterns of relations between cities in a systematic way by looking at the co-mentions of cities in text documents (here in web pages).  ...  part of the research, and Dr.  ... 
doi:10.7480/abe.2021.07.5793 fatcat:w4t4wcqntvdhfamhktkhcqzp4e