Results 11 to 20 of about 528,886 (272)
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 ...
Dłotko, Paweł +4 more
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Semantics-Preserving Bag-of-Words Models and Applications
IEEE Transactions on Image Processing, 2010 The Bag-of-Words (BoW) model is a promising image representation technique for image categorization and annotation tasks. One critical limitation of existing BoW models is that much semantic information is lost during the codebook generation process, an important step of BoW.
WU, Lei, HOI, Steven C. H., YU, Nenghai
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Image Reconstruction from Bag-of-Visual-Words [PDF]
2014 IEEE Conference on Computer Vision and Pattern Recognition, 2015 The objective of this work is to reconstruct an original image from Bag-of-Visual-Words (BoVW). Image reconstruction from features can be a means of identifying the characteristics of features.
Harada, Tatsuya, Kato, Hiroharu
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Albanian Text Classification: Bag of Words Model and Word Analogies [PDF]
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
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Decomposing Bag of Words Histograms [PDF]
2013 IEEE International Conference on Computer Vision, 2013 We aim to decompose a global histogram representation of an image into histograms of its associated objects and regions. This task is formulated as an optimization problem, given a set of linear classifiers, which can effectively discriminate the object categories present in the image.
Gandhi, Ankit +2 more
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Bag of ARSRG Words (BoAW) [PDF]
Machine Learning and Knowledge Extraction, 2019 In recent years researchers have worked to understand image contents in computer vision. In particular, the bag of visual words (BoVW) model, which describes images in terms of a frequency histogram of visual words, is the most adopted paradigm. The main drawback is the lack of information about location and the relationships between features. For this
Mario Manzo, Simone Pellino
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More than Bags of Words: Sentiment Analysis with Word Embeddings [PDF]
Communication Methods and Measures, 2018 Moving beyond the dominant bag-of-words approach to sentiment analysis we introduce an alternative procedure based on distributed word embeddings. The strength of word embeddings is the ability to capture similarities in word meaning. We use word embeddings as part of a supervised machine learning procedure which estimates levels of negativity in ...
Elena Rudkowsky +5 more
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Bag-of-Words for Transfer Learning
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021 Although the number of labeled datasets in Earth Observation (EO) is increasing, there is still a major gap between the Deep Learning (DL) classifiers designed in this field versus the models in Computer Vision. This gap is produced mainly by the number of datasets available, but also by the diversity of data.
Iulian, Calota +2 more
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Network-Based Bag-of-Words Model for Text Classification
IEEE Access, 2020 The rapidly developing internet and other media have produced a tremendous amount of text data, making it a challenging and valuable task to find a more effective way to analyze text data by machine. Text representation is the first step for a machine to
Dongyang Yan +3 more
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Improving Bag-of-Words model with spatial information [PDF]
, 2010 Bag-of-Words (BOW) models have recently become popular for the task of object recognition, owing to their good performance and simplicity. Much work has been proposed over the years to improve the BOW model, where the Spatial Pyramid Matching technique ...
Mayo, Michael, Zhang, Edmond Yiwen
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