Results 221 to 230 of about 528,886 (272)

Improved Arabic query expansion using word embedding. [PDF]

Sci Rep
Al-Lahham YA, Almatarneh S, Alshammari K, Al-Smadi M.   +3 more
europepmc   +1 more source

NeuroConText: Contrastive learning for neuroscience meta-analysis with rich text representation. [PDF]

Imaging Neurosci (Camb)
Ghayem F, Meudec R, Dockès J, Thirion B, Wassermann D.   +4 more
europepmc   +1 more source

A software pipeline for systematizing machine learning of speech data. [PDF]

Front Psychiatry
Celeste J, Tasnim M, Valdés Cuervo AJ, de la Cal EA, Stroulia E.   +4 more
europepmc   +1 more source

Detecting Redundant Health Survey Questions by Using Language-Agnostic Bidirectional Encoder Representations From Transformers Sentence Embedding: Algorithm Development Study.

JMIR Med Inform
Kang S, Park H, Taira R, Kim H.
europepmc   +1 more source

A computational validation for the health concept maturity levels questionnaire. [PDF]

Front Psychol
Trognon A, Habibi I, Altakroury H, Mahdar-Recorbet L, Poli A, Servais D, Lambert J, Béjean M, Abraham D.   +8 more
europepmc   +1 more source

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Bag-of-Words Similarity in eXplainable AI

2022
eXplainable AI (XAI) does not only lie in the interpretation of the rules generated by AI systems, but also in the evaluation and selection, among many rules automatically generated by large datasets, of those that are more relevant and meaningful for domain experts.
Narteni S, Ferretti M, Rampa V, Mongelli M   +3 more
openaire   +2 more sources

Improving Bag-Of-Words

Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, 2018
Bag-of-Words (BoW) is one of the important techniques for activity recognition. Instead of dividing a continuous sensor streams into sliding windows with fixed time duration, it builds activity recognition models using histograms of primitive motion symbols.
Ming Zeng, Tong Yu, Ole J. Mengshoel, Helen Qin, Chris Lee, John Paul Shen   +5 more
openaire   +1 more source

Beyond bag of words

Proceedings of the 21st ACM international conference on Multimedia, 2013
Due to the semantic gap, the low-level features are not able to semantically represent images well. Besides, traditional semantic related image representation may not be able to cope with large inter class variations and are not very robust to noise.
Chunjie Zhang, Shuhui Wang, Chao Liang, Jing Liu, Qingming Huang, Haojie Li, Qi Tian   +6 more
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Bag of visual words revisited

Proceedings of the Tenth International Workshop on Multimedia Data Mining, 2010
Visual information retrieval systems have gained importance due to the increasing amount of available digital multimedia data. Local features employing a bag of words approach from text retrieval have outperformed global features and have enhanced retrieval performance in large data sets. In this paper we conduct an exploratory study revisiting the bag
Marian Kogler, Mathias Lux
openaire   +1 more source

Word Image Retrieval Using Bag of Visual Words

2012 10th IAPR International Workshop on Document Analysis Systems, 2012
This paper presents a Bag of Visual Words (BoVW) based approach to retrieve similar word images from a large database, efficiently and accurately. We show that a text retrieval system can be adapted to build a word image retrieval solution. This helps in achieving scalability.
Ravi Shekhar, C.V. Jawahar
openaire   +1 more source