Results 11 to 20 of about 77,994 (293)
Log‐Euclidean bag of words for human action recognition [PDF]
IET Computer Vision, 2015 Representing videos by densely extracted local space–time features has recently become a popular approach for analysing actions. In this study, the authors tackle the problem of categorising human actions by devising bag of words (BoWs) models based on ...
Masoud Faraki +2 more
doaj +6 more sources
Persistence Bag-of-Words for Topological Data Analysis [PDF]
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019 Persistent homology (PH) is a rigorous mathematical theory that provides a robust descriptor of data in the form of persistence diagrams (PDs). PDs exhibit, however, complex structure and are difficult to integrate in today's machine learning workflows.
Zieliński, Bartosz +4 more
openaire +3 more sources
Multi-Document Summarization Using Distributed Bag-of-Words Model [PDF]
2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI), 2018 As the number of documents on the web is growing exponentially, multi-document summarization is becoming more and more important since it can provide the main ideas in a document set in short time. In this paper, we present an unsupervised centroid-based document-level reconstruction framework using distributed bag of words model.
Mani, Kaustubh +3 more
openaire +3 more sources
Tolerance Rough Set-Based Bag-of-Words Model for Document Representation
International Journal of Computational Intelligence Systems, 2020 Document representation is one of the foundations of natural language processing. The bag-of-words (BoW) model, as the representative of document representation models, is a method with the properties of simplicity and validity.
Dong Qiu, Haihuan Jiang, Ruiteng Yan
doaj +2 more sources
Bag-of-Words Technique in Natural Language Processing: A Primer for Radiologists. [PDF]
Radiographics, 2021 Juluru K +3 more
europepmc +2 more sources
Fuzzy Bag-of-Words Model for Document Representation
IEEE Transactions on Fuzzy Systems, 2018 One key issue in text mining and natural language processing is how to effectively represent documents using numerical vectors. One classical model is the Bag-of-Words (BoW). In a BoW-based vector representation of a document, each element denotes the normalized number of occurrence of a basis term in the document.
Rui Zhao, K. Mao
semanticscholar +3 more sources
Albanian Text Classification: Bag of Words Model and Word Analogies
Business Systems Research, 2019 Background: Text classification is a very important task in information retrieval. Its objective is to classify new text documents in a set of predefined classes, using different supervised algorithms.
Kadriu Arbana, Abazi Lejla, Abazi Hyrije
doaj +2 more sources
Multimodal Bag-of-Words for Cross Domains Sentiment Analysis [PDF]
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018 The advantages of using cross domain data when performing text-based sentiment analysis have been established; however, similar findings have yet to be observed when performing multimodal sentiment analysis. A potential reason for this is that systems based on feature extracted from speech and facial features are susceptible to confounding effecting ...
Nicholas Cummins +5 more
semanticscholar +3 more sources
Human Action Recognition Based on Bag-of-Words
Iraqi Journal of Science, 2020 Human action recognition has gained popularity because of its wide applicability, such as in patient monitoring systems, surveillance systems, and a wide diversity of systems that contain interactions between people and electrical devices, including ...
Riyadh Sahib Abdul Ameer, M. S. Altaei
semanticscholar +2 more sources
BoW3D: Bag of Words for Real-Time Loop Closing in 3D LiDAR SLAM [PDF]
IEEE Robotics and Automation Letters, 2022 Loop closing is a fundamental part of simultaneous localization and mapping (SLAM) for autonomous mobile systems. In the field of visual SLAM, bag of words (BoW) has achieved great success in loop closure.
Yunge Cui +5 more
semanticscholar +1 more source