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Accelerating Bag-of-Words with SOM
2019We propose a fast Bag-of-Words (BoW) method for image classification, inspired by the mechanism that arrangement of neurons in visual cortex can preserve the topology of mapping from inputs, and the fact that human brain can retrieve information almost instantly.
Jian-Hui Chen +2 more
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An Overview of Bag of Words;Importance, Implementation, Applications, and Challenges
International Enformatika Conference, 2019In the past fifteen years, the grow of using Bag of Words (BoW) method in the field of computer vision is visibly observed. In addition,-for the text classification and texture recognition, it can also be used in classification of images, videos, robot ...
W. Qader, M. M. Ameen, Bilal Ahmed
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Verdict Prediction for Indian Courts Using Bag of Words and Convolutional Neural Network
2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT), 2020All courts in India publish judgment by statistically analyzing the data of different cases and understanding the verdict from precedents judgments and the statute law.
V. Pillai, L. R. Chandran
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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 0001 +6 more
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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 0001 +6 more
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A Bag of Words Approach for 3D Object Categorization
2009In this paper we propose a novel framework for 3D object categorization. The object is modeled it in terms of its sub-parts as an histogram of 3D visual word occurrences. We introduce an effective method for hierarchical 3D object segmentation driven by the minima rule that combines spectral clustering --- for the selection of seed-regions --- with ...
Roberto Toldo +2 more
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Fuzzy bag of words for social image description
Multimedia Tools and Applications, 2014Rapid growth of social media resources brings huge challenges and opportunities for image description technologies. The performance of image description method directly affects the accuracy of image retrieval, image annotation and image recognition. Bag of Words (BoW) as an efficient approach to describing the images has been attracting more and more ...
Yanshan Li +3 more
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Contextual Bag-of-Words for Robust Visual Tracking
IEEE Transactions on Image Processing, 2018An appearance model is critical for most modern trackers. While numerous novel appearance models have been proposed with demonstrated success, challenges such as occlusion and drifting are still not well addressed. In this paper, we propose a novel contextual bag-of-words (CBOW) discriminative appearance model that appropriately handles drifting and ...
Fanxiang Zeng +2 more
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A hybrid feature extraction approach for brain MRI classification based on Bag-of-words
Biomedical Signal Processing and Control, 2019Magnetic resonance imaging (MRI) has attracted considerable attention in medical engineering community, since it is a non-invasive diagnostic technique and for its importance in medicine applications.
Wadhah Ayadi +3 more
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Incorporating temporal context in Bag-of-Words models
2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), 2011Bag-of-Words (BoW) is a highly popular model for recognition, due to its robustness and simplicity. Its modeling capabilities, however, are somewhat limited since it discards the spatial and temporal order of the codewords. In this paper we propose a new model: Contextual Sequence of Words (CSoW) which incorporates temporal order into the BoW model for
Tamar Glaser, Lihi Zelnik-Manor
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Image Representation with Bag-of-Words
2016Image classification, which is to assign one or more category labels to an image, is a very hot topic in computer vision and pattern recognition. It can be applied in video surveillance, remote sensing, web content analysis, biometrics, etc. Many successful models transform low-level descriptors into richer mid-level representations.
Xiang Xu, Xingkun Wu, Feng Lin
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